AI Engineer Jobs

AI Engineer / Senior AI Engineer

Blue Matter

South San Francisco, CA

Blue Matter is a rapidly growing management consultancy focused on the biopharmaceutical industry.We partner with clients to help them achieve commercial success across the lifecycle of their products, portfolios, and organizations.Blue Matter is hiring for the Technology and Operations Practice wit...

AI Engineer

Gen AI Enable

Remote

AI Engineer I – Early Career / New Graduate Company: Gen AI Enable, LLC Location: Remote (United States) | Pennsylvania Headquarters Employment Type: Full-Time, W-2 Starting Salary: $74,000–$84,000 annually Travel: Up to 10% for occasional client meetings and workshops About Gen AI Enable Gen AI Enable, LLC is an AI professional services firm and product company helping mid-market and enterprise organizations move from AI curiosity to AI in production. Our consulting practice spans four service lines: AI Enablement & Education, AI Strategy, AI Acceleration Center, and AI Application Lifecycle Management & Governance. We also develop Dextruss, our multi-agent orchestration platform designed to automate customer journeys through intelligent AI agents. We are a small, experienced team that builds and delivers real solutions. Our engineers are involved throughout the entire process, from understanding client challenges and designing solutions to developing applications and delivering measurable results. About the Role We are seeking an AI Engineer I to join our growing team. This is an excellent opportunity for a recent college graduate or early-career engineer who is passionate about artificial intelligence, software development, and building innovative technology solutions. You will work alongside senior engineers to design, build, test, and deploy production-ready AI applications and intelligent agent systems for enterprise clients. You will gain hands-on experience with large language models (LLMs), multi-agent systems, AI-assisted software development, and enterprise technology integrations. This role combines software engineering, applied AI development, and client-facing consulting, providing exposure to the full lifecycle of AI solution delivery. We provide mentorship, a structured development plan, and performance evaluations at 90 days, 180 days, and annually, with opportunities for increased responsibility and compensation growth. Key Responsibilities Software Engineering & AI-Assisted Development Design, develop, test, and deploy scalable applications using Python and TypeScript/JavaScript. Use AI development tools such as Claude Code, GitHub Copilot, and Cursor to improve development productivity and quality. Follow software engineering best practices, including Git version control, code reviews, automated testing, and CI/CD. Validate, understand, and take ownership of AI-generated code. AI Agents & Multi-Agent Systems Develop AI agents that interact with APIs, retrieve information, use tools, and collaborate with other agents. Implement prompt engineering strategies, structured outputs, retrieval-augmented generation (RAG), guardrails, and error handling. Build and execute evaluations to measure AI agent performance and reliability. Integrate AI applications with enterprise platforms, including CRM, ERP, ticketing, and data systems. Client Solutions & Consulting Collaborate with senior engineers and architects to translate business requirements into technical solutions. Develop proofs of concept (POCs) and minimum viable products (MVPs). Participate in client meetings, technical demonstrations, and workshops. Communicate project progress, technical challenges, and results clearly and proactively. Quality, Documentation & Governance Write and maintain technical documentation, including READMEs, runbooks, and change histories. Follow security, data privacy, and responsible AI governance standards. Participate in peer code reviews and continuous improvement initiatives. Professional Development Follow a structured learning and development plan. Pursue relevant technical certifications. Stay current with emerging AI technologies, frameworks, and development tools. Share knowledge and contribute to a collaborative engineering culture. Required Qualifications Education & Experience Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Data Science, or a related technical field. Equivalent demonstrated technical experience or project work will also be considered. 0–2 years of professional experience. Internships, co-ops, academic research, and substantial personal projects are valued. A portfolio of technical work, such as GitHub repositories, capstone projects, hackathon submissions, or other software applications, that you can discuss during an interview. Technical Skills Proficiency in at least one modern programming language, preferably Python or TypeScript/JavaScript. Understanding of software engineering fundamentals, including data structures, algorithms, testing, and debugging. Experience using Git and collaborative development workflows. Familiarity with REST APIs, JSON, SQL, and relational databases. Artificial Intelligence Experience Hands-on experience using AI coding assistants such as Claude Code, GitHub Copilot, or Cursor. Experience developing at least one application or project using an LLM API, such as Anthropic Claude or OpenAI. Understanding of prompt engineering and how prompt design influences AI model outputs. Awareness of AI model limitations, including hallucinations, context limitations, and the importance of validating generated outputs. Professional Skills Strong written and verbal communication skills. Ability to explain technical concepts to both technical and non-technical audiences. Strong problem-solving skills, curiosity, and willingness to learn. Ability to take ownership of assigned work and collaborate effectively. Comfortable working in a fast-paced environment where requirements may evolve. Must be legally authorized to work in the United States without current or future visa sponsorship. Preferred Qualifications The following qualifications are beneficial but not required: Software engineering or technology consulting internship experience. Familiarity with retrieval-augmented generation (RAG), function calling, tool calling, and AI evaluation frameworks. Exposure to AI agent frameworks or orchestration libraries. Experience with AWS (Lambda, S3, ECS, Bedrock) or Microsoft Azure AI services. Familiarity with Docker, containerization, and CI/CD pipelines. Front-end development experience with React or Next.js. Exposure to enterprise platforms such as Salesforce, Oracle Cloud Fusion, HubSpot, or Zendesk. Certifications such as AWS Certified Cloud Practitioner or Microsoft Azure AI Fundamentals. Interest in customer success, enterprise operations, and AI-driven business transformation. Our Technical Environment You will have the opportunity to work with technologies including: Programming: Python, TypeScript, JavaScript, SQL AI Platforms: Anthropic Claude API and other LLM providers AI Development Tools: Claude Code, GitHub Copilot Cloud & Infrastructure: AWS, Azure, Docker, CI/CD AI Platform: Dextruss multi-agent orchestration platform Enterprise Integrations: Salesforce, HubSpot, Zendesk, and other enterprise systems Collaboration Tools: GitHub, ClickUp, Linear, Slack, SharePoint What Makes This Opportunity Unique At Gen AI Enable, you won't just observe AI innovation — you'll help build it. As an early-career engineer, you will have the opportunity to: Work directly with experienced technical leaders and senior engineers. Build real AI applications used by enterprise clients. Gain hands-on experience with emerging generative AI and agent technologies. Participate in both client consulting engagements and internal product development. Develop technical and professional skills through structured mentorship. Take meaningful ownership of projects early in your career. Grow alongside a company focused on practical, production-ready AI solutions. If you're a motivated early-career engineer who enjoys solving problems, learning new technologies, and building real-world AI applications, we encourage you to apply.

AI Engineer

Max AI, Inc.

Ann Arbor, MI

Max AI – Stripe for Healthcare Max AI is the World’s first human-free, fully-autonomous medical billing AI agent. Many startups are attempting to attack this problem because the market is so big — $350B/yr. We have the best team going after it. While everyone else still needs humans in the loop, we’ve cracked the code for medical billing starting with dermatology, and are rapidly adding support for every other specialty. Medical doctors who code are rare. We have the best one in the world. His previous apps have driven 50M+ downloads, all while running an incredibly successful practice of his own where he literally did the billing by hand himself. Our Head of AI has been doing AI research at MIT and Caltech for over 10 years. And our Head of Engineering was one of the earliest engineers at Figma. AI Engineer Responsibilities Build, experiment, and evaluate AI agents and ML models in the NLP domain to improve the accuracy of medical coding/billing and other aspects of revenue cycle management. Contribute to the building of internal AI frameworks to enable the building of our AI agents and ML models Collaborate closely with a small, high-impact team and engage directly with our Operations team and our customers to drive meaningful improvements. Work Approach Complete product ownership: tackle challenges across the board rather than working in silos. An agile, iterative process with clear accountability. Regular interactions with customers to ensure our product continuously evolves to meet their needs. Core Values A proactive mindset: Spot and resolve issues, continuously driving improvements. Commitment to lifelong learning and personal growth. Positivity, collaboration, and a team-first attitude. Clear communication skills Requirements Required 6+ years of ML/AI/data science in a production setting Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) Expertise in AI/ML and specifically in NLP (pre-processing, embeddings, transformer-based models, etc) Experience with LLM, including supervised fine-tuning, usage of AI frameworks, evaluations of LLMs Nice to Have Experience working at high-growth startups Exposure in highly regulated industries and/or healthcare Experience with AWS Benefits Compensation $150k - $250k USD Equity Platinum Healthcare Medical (Platinum PPO) Company covers 100% for employee, 80% for dependents Dental (Platinum PPO) Company covers 90% for employee, 75% for dependents Vision (Platinum PPO) Company covers 90% for employee, 75% for dependents Perks $250 per month (gym membership, classes, etc) $2,000 annually (courses, mentorship, etc)

AI Engineer

Tata Consultancy Services

Remote

Role - AI Engineer Location: We are hiring for roles across multiple locations within the United States. About the Role We are looking for a passionate and driven AI Engineer to join our growing AI team in the United States. In this role, you will collaborate with experienced engineers and architects to design, build, and deploy innovative AI/ML and Generative AI solutions. This is an exciting opportunity to gain hands-on experience across the entire AI lifecycle—from data preparation and model development to evaluation and real-world deployment—while working on cutting-edge technologies such as LLMs, RAG pipelines, and agentic AI systems. Key Responsibilities Assist in building, training, and fine-tuning machine learning and Generative AI models Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) Develop AI-powered applications using Python and common ML frameworks Evaluate LLM outputs for accuracy, quality, factuality, and bias Document model behavior, dataset usage, and training workflows for reproducibility Collaborate with cross-functional teams (product, engineering, data) for testing and integration Stay up to date with the latest AI advancements, tools, and research trends Education Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, IT, Data Science, or related fields Technical Skills Programming & Machine Learning Strong proficiency in Python Hands-on experience with NumPy, Pandas, Scikit-learn Basic understanding of TensorFlow or PyTorch GenAI & LLM Foundations Familiarity with LLMs, embeddings, and prompt engineering Understanding of GPT, BERT, and generative models such as GANs, VAEs, Diffusion models Tools & Frameworks Exposure to LangChain, Hugging Face, OpenAI APIs, Azure OpenAI Service Cloud & Advanced AI Concepts Awareness of Azure AI, AWS Bedrock, Google Vertex AI Basic understanding of RAG pipelines, vector databases (Pinecone, FAISS) Knowledge of Agentic AI and Model Context Protocol (MCP) fundamentals Familiarity with CI/CD practices for AI workflows Responsible AI & Quality Awareness of AI fairness, bias, privacy, and responsible AI principles Understanding of model evaluation metrics and LLM-specific challenges such as hallucination detection and factual accuracy Soft Skills Strong curiosity and eagerness to learn Effective communication and collaboration skills Analytical thinking with a structured problem-solving approach Willingness to experiment, iterate, and innovate Nice-to-Have (Preferred) Certifications such as: Azure AI Engineer Associate AWS Machine Learning Specialty Google Professional ML Engineer Databricks certifications Internship or academic project experience in AI/ML or Generative AI Why Join Us Work on cutting-edge AI and GenAI initiatives Gain mentorship from experienced AI architects and engineers Exposure to real-world, large-scale AI deployments Dynamic, innovative, and collaborative work environment across the U.S.

Bridgeway is seeking an AI Engineer to help build and operate large language model and intelligent automation capabilities across our products and internal tooling. The AI Engineer will implement production systems against the patterns and reference implementations set by our architecture team, contribute to design discussions, and partner with senior engineers to ship reliable AI-enabled features. This is a hands-on engineering role focused primarily on building. We are seeking a technically curious individual who brings solid Python experience and a pragmatic approach to AI-enabled capabilities. A successful AI Engineer is a strong builder with a growing background in production software development and the kind of engineering judgment that turns architectural patterns into reliable working systems. This is a remote position with preference given to East Coast candidates. Responsibilities: Contribute to the technical direction for AI-enabled systems at Bridgeway, in partnership with senior engineers and the architecture team. Participate in design reviews for AI-adjacent features and incorporate feedback from senior engineers and architects. Build production-quality Python services, pipelines, and integrations that apply LLMs and retrieval to concrete internal and product problems. Integrate LLM APIs into existing systems, following established guidance on model selection, cost profile, and failure-handling for each use case. Ensure AI capabilities correctly honor schema-per-tenant and PHI-boundary patterns within our multi-tenant model, partnering with the data team that owns those patterns. Partner with the data and analytics team to integrate retrieval- and LLM-backed features into the lakehouse and analytics layer — embedding and chunking choices, retrieval evaluation, semantic search, summarization, anomaly narration, and contextual guidance for fund office users — with the data team owning pipeline build and operation. Contribute to prompt libraries, evaluation frameworks, reference implementations, and reusable components that help engineers ship AI-touching features consistently and safely; follow and help refine development standards for model selection, evaluation, testing, observability, and cost management. Help evaluate emerging AI tools and provide input on build-vs-buy decisions anchored in Bridgeway's technical, cost, and compliance context. Build AI implementations that comply with HIPAA, SOC 2, and NIST — with particular attention to PHI handling, data residency, audit logging, and BAA coverage — and work with information security to apply AI-specific controls including prompt-injection defenses, DLP for LLM interactions, model access governance, and secrets handling. Maintain documentation of AI systems, data flows, and risk assessments sufficient for audit and compliance review. Collaborate with engineering, product, customer success, security, data, and operations to identify automation opportunities, help translate them into technical plans, and contribute to the roadmap for future customer-facing AI capabilities. Participate in the operational quality and on-call rotation for AI systems — including incident response, post-incident learning, and instrumented observability — and help build feedback loops from users to continuously refine retrieval quality, prompt behavior, and agent reliability. Track cost, quality, and adoption metrics for AI systems in production and report outcomes to your manager, the architecture team, and the team leads. Apply best practices in enterprise AI-integration and share knowledge with peers. Qualifications: 3–5 years of software engineering experience, with at least one year working on AI- or ML-backed systems, including contributions to at least one LLM-backed system in production. Working knowledge of programmatic LLM orchestration, evaluation frameworks, and agent and tool-using systems, including exposure to securely connecting enterprise APIs to agentic systems. Strong Python skills for production services, data pipelines, and integration work. Experience building retrieval-augmented systems including familiarity with enterprise data architectures such as Databricks and Azure/AWS. Strong written and verbal communication. Familiarity with CI/CD, infrastructure-as-code, and MLOps practices for AI/ML systems. Experience using generative AI tools such as Claude and Copilot to improve productivity and deliver high-quality outcomes Production experience in a regulated industry, with practical familiarity with HIPAA, SOC 2, or NIST, and with multi-tenant SaaS data isolation and identity/access patterns for B2B platforms (preferred). Bachelor's or master's degree in Computer Science, Engineering, Data Science, or related field. Bridgeway is an Equal Opportunity Employer.

AI Field Engineer - AI Natives | Fireworks AI Role Summary Fireworks AI is hiring senior AI Field Engineers to help AI-native customers adopt and scale its generative AI platform. This role combines sales engineering with forward-deployed engineering and owns technical discovery, workshops, proof-of-concepts, integration, and performance work. Responsibilities • Lead technical discovery, demos, POCs, POVs, and customer workshops. • Integrate the Fireworks platform into customer AI/ML systems. • Partner with customers on architecture, performance engineering, and production deployment. • Translate business requirements into practical AI solutions and maintain strong client relationships. • Work cross-functionally with sales, product, and engineering teams. Required Qualifications • 5-10 years of relevant experience; senior individual contributor ready to lead. • Experience at a top-tier AI-native company. • Customer-facing pre-sales experience as a Solutions Architect, Sales Engineer, TAM, Engineering Manager, or Product Manager. • Strong AI/ML depth, including fine-tuned LLMs, generative AI infrastructure, or hyperscaler AI services. • Demonstrated success building and maintaining production systems. • Excellent client management and communication skills. Preferred Qualifications • Kubernetes, ML engineering, and product thinking. • Experience with complex enterprise AI deployments. Employment Details • Full-time; 8-10 openings. • Remote, with New York and San Francisco candidates preferred. • Regular enterprise customer travel may be required. • Base salary: $176,000-$228,000. • OTE: $220,000-$285,000.

AI Engineer

Trilogy

Remote

Are you a seasoned software engineer with a deep interest in AI? Trilogy is on the lookout for exceptional engineers to lead the charge in adopting generative AI tools both in our development process and into our products. Join us to work on our exciting product portfolio: TeachTap: Bringing historical figures to life using AI, offering an engaging, TikTok-like learning experience to make learning more relevant and fun. Educational Content Generation: Utilizing the latest in generative AI combined with comprehensive learning materials to create captivating content. TeachTower: A game-based motivation system inspired by popular games like Roblox and Minecraft, designed to make learning irresistibly fun. Coachbot: A learning copilot that integrates with existing apps, guiding learning paths, recommending next steps, and rewarding daily progress. Data-driven Sales: A sales platform that leverages AI to provide real-time guidance to agents during calls, create personalized renewal plans, and quality control sales calls. Crossover: An AI-powered hiring platform that sifts through millions of applicants annually to find the top 1% of global talent. Your role will focus on integrating AI into engineering practices, using AI tools to increase efficiency and solve engineering tasks like coding and testing. Based on the obtained results, you will derive recipes and playbooks to be adopted by the broader engineering team. Maintaining high-quality standards in our codebases while ensuring high leverage of AI tools across our engineering teams will be a key part of your work. You will be an integral part of our existing engineering team, working collaboratively on our suite of products to deeply understand our environment and needs. You will have the freedom to propose and experiment with new tools and then will leverage the insights and experiences obtained to evolve our processes, advocate for new tool adoption, or even spearhead the creation of small tools, bots, and frameworks to enhance our technical setup. We seek candidates with a strong background in software engineering and a capacity for adapting to new technologies. Moreover, an interest in the latest generative AI developments and a drive for innovation are crucial. While our primary tech stack is AWS Serverless with TypeScript, we're looking for versatile engineers who can excel in a variety of technical environments and challenges. Developing fully functional features, using AI tools to expedite delivery and enhance quality. Performing experiments with AI to enhance engineering processes, including decomposition, solution design, code generation, and troubleshooting. Documenting best practices and techniques in guides that enable others to harness the power of generative AI effectively. Drive transformative change by establishing a framework that seamlessly integrates generative AI, significantly amplifying engineering productivity. Leading a team of AI-first engineers, evaluating experiments, documenting findings, selecting the best methodologies, implementing them team-wide, establishing processes, and staffing this team. At least 5 years of experience in professional software development. At least 3 years of experience as either a lead engineer reviewing the work of other engineers or as an architect making important technical decisions. Excited to use and explore new generative AI tools for software engineering tasks on a day-to-day basis.

AI Engineer

Tata Consultancy Services

Santa Clara, CA

AI Engineer (Entry-Level) Location - Santa Clara, CA As an AI Engineer, you will work closely with senior AI engineers and architects to build, test, and deploy AI/ML and GenAI solutions. This role provides hands-on exposure to data preparation, model development, evaluation, and integration of AI systems with business applications. Key Responsibilities Assist in developing and training machine learning and GenAI models under guidance. Perform data preprocessing, feature engineering, and exploratory data analysis. Support development of AI applications using Python and standard ML frameworks. Contribute to evaluating LLM outputs for quality, accuracy, factuality, and bias. Document model behavior, datasets, training processes, and versioning. Collaborate with cross-functional teams for model testing and integration. Stay updated with emerging AI technologies, tools, and research trends. Education Bachelor’s or Master’s degree in Computer Science, IT, Data Science, or related fields. Technical Skills (AI & GenAI Focus) Programming & ML Basic programming skills in Python. Understanding of NumPy, Pandas, and Scikit-learn. GenAI & LLM Concepts Familiarity with LLMs, embeddings, and prompt engineering. Cloud & Advanced Topics Awareness of AWS Bedrock. Basic understanding of RAG pipelines, vector databases (Pinecone, FAISS), agentic AI, and Model Context Protocol (MCP). Quality, Safety & Ethical AI Awareness of AI fairness, bias, privacy, and responsible AI principles. Familiarity with model evaluation metrics and LLM-specific checks such as hallucination and factuality assessments. Soft Skills Curiosity and a strong learning mindset. Good communication skills and the ability to work with cross-functional teams. Problem-solving ability with a structured approach and willingness to iterate on prototypes.

Crogl Fully Autonomous AI Team Member for Your SOC Crogl is building AI-powered systems that help security teams investigate, understand, and respond to threats faster. We combine advances in large language models, agent architectures, and security expertise to create intelligent systems that solve real-world problems for security practitioners. We’re looking for AI Engineers who are excited about building practical AI products. You’ll help design, evaluate, and improve agentic systems that operate in production, working closely with customers, engineers, and product teams to push the boundaries of what’s possible with modern AI. What you’ll be doing: Build LLM-powered features, workflows, and agentic systems that solve real customer problems. Design and implement evaluation frameworks to measure agent quality, reliability, and business impact. Create automated benchmarks, regression tests, and datasets for evaluating AI behavior. Investigate agent failures and develop systematic approaches to improve performance. Experiment with prompting, tool use, retrieval, memory, planning, and reasoning strategies. Build infrastructure that supports rapid experimentation, evaluation, deployment, and monitoring. Work closely with customers and internal teams to understand workflows and identify opportunities for AI automation. Contribute to engineering best practices for testing, observability, and production reliability. Stay current with advances in LLMs, agents, evaluation methodologies, and AI engineering. A core part of this role: evaluating AI systems Building agents is only half the challenge. Understanding whether they are actually improving is equally important. A significant portion of this role involves designing and maintaining evaluation systems for AI agents operating in real-world security workflows. You’ll help answer questions like: Is the agent producing accurate investigations? Are changes to prompts, tools, or models actually improving outcomes? How do we detect regressions before customers experience them? Which failure modes matter most? How do we measure reliability, trustworthiness, and business impact? You’ll build benchmarks, datasets, automated evaluations, regression testing pipelines, and observability systems that help us continuously improve agent performance. What you’ll bring to the team: Strong programming skills, preferably in Python. Solid software engineering fundamentals, including testing, debugging, and system design. Experience building applications, projects, or products using LLMs and modern AI tools. Ability to design experiments, interpret results, and make data-driven decisions. Strong communication skills and willingness to collaborate across disciplines. Curiosity, ownership, and a desire to learn quickly. What makes you stand out from others: Experience building AI agents, copilots, or workflow automation systems. Experience designing evaluations, benchmarks, or testing frameworks for AI systems. Familiarity with OpenAI, Anthropic, Gemini, or open-source LLM ecosystems. Experience with retrieval systems, vector databases, and RAG architectures. Familiarity with LangGraph, OpenAI Agents SDK, MCP, or similar agent frameworks. Experience with observability, tracing, and production monitoring for AI systems. Exposure to cybersecurity, security operations, or developer tooling. Open-source contributions, research projects, or personal AI products. Example projects: Building evaluation suites that measure the quality of AI-driven security investigations. Creating automated regression tests to detect model and prompt regressions. Improving agent reasoning, planning, and tool-use capabilities. Developing datasets and benchmarks that reflect real customer workflows. Building systems that automatically identify and categorize agent failures. Designing feedback loops that continuously improve production agent performance. Who thrives at Crogl: The strongest candidates for this role are usually builders. You may have experience as a software engineer, ML engineer, researcher, AI engineer, or founder. What matters most is your ability to learn quickly, work independently, and ship impactful systems. We’re particularly excited about candidates who have: Built and deployed AI agents. Created evaluation frameworks for LLM applications. Published AI projects, demos, or open-source contributions. Developed tools that other people actively use. Strong opinions about what makes AI systems reliable and useful. If you’ve spent nights and weekends building AI products because you genuinely enjoy it, you’ll probably fit in well here. What we value: We care more about demonstrated ability than specific credentials. You might be a great fit if you’ve: Built AI products, agents, or developer tools that people actually use. Created evaluation frameworks, benchmarks, or testing systems for LLM applications. Contributed to open-source AI projects. Conducted independent research or published technical writing. Built ambitious side projects and iterated on them based on real-world feedback. Shown exceptional curiosity and a track record of learning quickly. We’re especially interested in candidates who can show us what they’ve built. GitHub repositories, demos, blog posts, open-source contributions, benchmarks, evaluation frameworks, AI products, and side projects are all valuable signals. We don’t expect candidates to check every box. If you’re excited about the role and believe you can contribute, we’d encourage you to apply. What success looks like: Within your first six months, you will: Ship improvements to production AI systems used by customers. Help establish rigorous evaluation practices across the company. Contribute new ideas that improve agent performance and reliability. Develop a strong understanding of customer workflows and security investigations. Become a trusted contributor across engineering, product, and AI initiatives. Why Crogl? Work on some of the most challenging problems in applied AI. Help define how agentic systems are evaluated and deployed in production. Join a small, highly collaborative team with significant ownership and impact. Learn quickly while working alongside experienced engineers, researchers, and security experts. Shape the future of AI-powered security operations.

AI Engineer

Tata Consultancy Services

Remote

Job Title- AI Engineer Location- Chicago, IL Salary Range- 70k to 90k About the Role We are seeking a motivated and technically strong early-career professional with advanced Python skills and knowledge on machine learning projects and AI-focused internships (preferred) during undergraduate or master’s studies. The ideal candidate should be passionate about applying machine learning and agentic AI techniques to real-world problems, thrive in collaborative environments, and have the curiosity to explore new AI methods and tools. Key Responsibilities · Contribute to the design, build, deployment, and optimization of AI/GenAI/Agentic AI solutions for customers as well as internal TCS AI and Data business platforms. · Design, train, and optimize machine learning models for classification, regression, NLP, or computer vision tasks. · Write clean, efficient, and well-documented Python code for data preprocessing, model training, and deployment. · Work with large datasets: clean, transform, and analyze structured and unstructured data. · Collaborate with cross-functional teams (data engineers, researchers, and product managers) to integrate AI/ML solutions into applications and workflows. · Conduct experiments, evaluate model performance, and present findings with clear metrics and visualizations. · Stay updated on emerging AI/ML and Agentic AI research and contribute innovative ideas to improve products and processes. Required Qualifications · Bachelor's or master's degree in computer science or related field. · Strong Python programming skills · Academic experience in machine learning, AI, or data-driven projects. · Understanding of algorithms, data structures, and machine learning concepts. · Familiarity with version control (Git) and Jupyter/VS Code workflows. Preferred Qualifications · Experience with deep learning (CNNs, RNNs, Transformers) or natural language processing. · Exposure to cloud platforms (AWS, GCP, Azure) or MLOps tools (Docker, MLflow, Kubernetes). · Contributions to open-source projects or published research in AI/ML. · Strong analytical and problem-solving skills with attention to detail. What We Offer · Opportunity to work on impactful AI/ML and Agentic AI projects. · Mentorship from experienced AI scientists and engineers. · A collaborative and inclusive culture that values innovation and curiosity. · Growth pathways into specialized AI/ML engineering, research, or applied data science roles.

Required Skills & Experience 8+ years of software engineering experience. Strong hands-on development experience with .NET and Python. Experience building customer-facing AI products used by end users. Experience taking AI solutions from concept through production deployment. Experience with LLMs, agents, RAG, vector databases, embeddings, and prompt engineering. Full-stack development experience including modern web UI development. Cloud experience in Azure, AWS, and/or Databricks. Ability to lead initiatives and influence technical direction across teams. Product-minded engineer who thinks about user experience, adoption, and business value. Nice to Have Skills & Experience Recommendation engine, or personalization experience. Experience building AI features for web and mobile applications. Angular or modern frontend framework experience. Multi-agent orchestration and MCP experience. Experience improving engineering productivity through AI-assisted development tools. Startup, entrepreneurial, or "builder" mindset. Demonstrated thought leadership around AI product strategy and innovation. Prior experience serving as a technical lead or team lead. Job Description Insight Global is seeking an AI Engineer for one of our clients. This person will: Build AI-powered features for the web and mobile experiences. Design and develop AI agents, copilots, RAG applications, and workflow automations. Develop across the full stack including UI, APIs, backend services, and cloud infrastructure. Partner with Product, Data Science, Architecture, and Security teams to bring AI products to production. Prototype new AI use cases and recommend future product capabilities. Lead technical direction and mentor engineers on AI engineering best practices. Extend and enhance existing production AI platforms and customer-facing AI experiences. We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to Human Resources Request Form. The EEOC "Know Your Rights" Poster is available [here](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf).

Core Technical Skills Strong experience building AI-enabled applications in production environments. Experience with speech-to-text/transcription pipelines or similar AI workloads. Hands-on experience with LLMs, prompt engineering, and evaluation workflows. Experience designing AI pipelines and data processing workflows. Engineering & DevOps Experience with CI/CD pipelines and DevSecOps practices. Knowledge of API integration and microservice architectures. Experience implementing observability and monitoring for AI systems. Judicial Transcribe is an AI-enabled platform designed to deliver automated transcription and AI-assisted processing of judicial audio recordings. The service is already deployed at scale and is now entering the next phase of operational maturity. The current focus is to stabilise the live service, strengthen engineering resilience, and extend capabilities including transcription from uploaded audio files, anonymisation/redaction, and AI-driven summarisation. The programme also acts as a testbed for evolving AI engineering practices, helping to establish reusable patterns for future AI-enabled products and services. To support this phase, the team is seeking two experienced AI Engineers for an initial six-month engagement. Role Focus The AI Engineer will focus on AI capability development and production maturity, helping to improve reliability, scalability, and engineering practices across the service. You will work closely with engineers, product teams, and delivery leads to expand core functionality while ensuring robust, secure, and well-governed AI workflows., AI Service Development Support and enhance the live Transcribe service, focusing on AI components. Design and implement transcription workflows for uploaded audio files. Develop anonymisation and redaction capabilities aligned with publication requirements. AI Integration & Capabilities Support the transcript summarisation proof of value (PoV). Enable reuse of existing summarisation capabilities through API-based integration. Work with internal API platforms to expose and consume AI capabilities. AI Engineering Practices Strengthen AI pipeline patterns including: Extract - Chunk - Prompt - Evaluate workflows Integrate evaluation mechanisms and Responsible AI controls into AI features. Contribute to the safe and structured use of AI coding assistants within the development life cycle. DevSecOps & Operational Maturity Improve AI-specific CI/CD practices, testing frameworks, and deployment processes. Enhance observability, monitoring, and production readiness for AI services. Support improvements in system resilience and operational stability. Knowledge Sharing & Engineering Resilience Reduce single-point-of-failure risks by documenting systems and sharing knowledge. Contribute to engineering standards, documentation, and operational playbooks. Expected Outcomes During the six-month engagement the team aims to deliver: Stable and sustainable live support capability for the Transcribe platform. Delivery of audio file transcription capability. Delivery or controlled rollout of anonymisation/redaction features. Clear integration Pathway for transcript summarisation services via API. Improved deployment confidence and release cadence. Reduced dependency on individual engineers through improved documentation and shared knowledge. Strengthened AI engineering practices and operational maturity across the service

At Lightrun, we’re closing the gap between AI-generated code and real-world runtime behavior. Our platform restores the critical verification loop in enterprise environments by enabling safe, real-time observability - logs, metrics, and traces injected on demand into live systems - so engineers and AI agents can validate assumptions where code actually runs.Backed by Accel and Insight Partners, and trusted by leaders like Microsoft, Salesforce, Citi, and SAP, Lightrun is building the runtime foundation for the next era of agentic software development. Join us to build cutting-edge systems, collaborate with world-class engineers, and shape how autonomous software is built in production. We are looking for an AI Engineer to join the hunt. Responsibilities : Take part in the design and development of AI-driven features for our Dev-Native Observability Platform. Collaborate with cross-functional teams to integrate AI solutions into existing systems. Contribute to the product roadmap by identifying AI opportunities and providing insights as a potential end user Stay updated with the latest AI trends and technologies to ensure our platform remains cutting-edge. Requirements : At least 3 years experience in Python / TS working with AI/ML frameworks At least 5 years of backend experience with at least one additional programming language (Java / C# / Node.js / C++) At least 3 years experience working with database solutions (RDBMS, NoSQL, Vector) Proven experience with writing efficient and useful LLM prompts Proven experience building LLM-based solutions and integrating them into products Strong system and architecture design skills, particularly in designing LLM based systems Experience or at least substantial knowledge of GenAI technologies such as agentic flows, RAG, model fine-tuning / distilling, prompt engineering, context engineering Hands-on experience with cloud platforms and their AI/LLM services Experience working on a SaaS product - Advantage Experience working with customers and direct customers feedback - Advantage Experience using observability / profiling / remote debugging tools - Advantage Passionate about AI and up to date with industry trends - Advantage

AI Engineer

Particle41

United States

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language Models (LLMs). Experience deploying models into production: building REST APIs, microservices and monitoring. Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc. Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI. Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker). Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models). Ability to work in a fast-paced, dynamic environment and adapt to changing priorities. Publications, open-source contributions, or personal projects in the AI/ML domain About Particle41 Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE ) E - Empowering: Enabling individuals to reach their full potential. L - Leadership: Taking initiative and guiding each other toward success. I - Innovation: Embracing creativity and new ideas to stay ahead. T - Teamwork: Collaborating with empathy to achieve common goals. E - Excellence: Striving for the highest quality in everything we do. We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring. We appreciate your interest and encourage applicants from these regions to apply. If you need any assistance during the application or interview process, please feel free to reach out to us at . Originally posted on Himalayas

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language Models (LLMs). Experience deploying models into production: building REST APIs, microservices and monitoring. Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc. Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI. Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker). Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models). Ability to work in a fast-paced, dynamic environment and adapt to changing priorities. Publications, open-source contributions, or personal projects in the AI/ML domain About Particle41 Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE ) E - Empowering: Enabling individuals to reach their full potential. L - Leadership: Taking initiative and guiding each other toward success. I - Innovation: Embracing creativity and new ideas to stay ahead. T - Teamwork: Collaborating with empathy to achieve common goals. E - Excellence: Striving for the highest quality in everything we do. We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring. We appreciate your interest and encourage applicants from these regions to apply. If you need any assistance during the application or interview process, please feel free to reach out to us at careers@Particle41.com.

AI Engineer

ELSA Speak

United States

Department: Gen AI & LLM Team Location: Remote Job Type: Full Time About Us: Founded in 2016, ELSA harnesses the power of generative AI to improve English communication skills globally, with headquarters in San Francisco and offices in Lisbon, Tokyo, Jakarta, Singapore, and Vietnam. With over 50 million users and 1 billion hours of anonymized data, our AI-driven language learning platform delivers hyper-personalized learning paths for both businesses and individuals, transforming lives and organizations through effective spoken English. ELSA is backed by leading investors including Gradient VenturesGoogles AI fund, Monk's Hill Ventures, and Global Ventures. At ELSA, our vision is to be the global leader in teaching real-time, conversational English, with the aim of helping over 1.5 billion language learners worldwide. We are here to celebrate and empower every individual on the global stage to build confidence, be understood, and share their story. Come join our very talented team of people working to make a difference with our proprietary speech recognition and AI-driven language learning technology! About the role: You will be joining the AI Research Team, a group of experts dedicated to advancing AI-driven language learning technologies. We are seeking an AI Engineer to drive the development and deployment of LLM-powered capabilities at ELSA. This role sits at the intersection of software engineering and machine learning, focusing on delivering high-quality AI systems that enhance ELSAs conversational tutoring experience. The ideal candidate is a pragmatic AI engineer and an agent of change, pushing the team towards a 3x acceleration in AI-driven development, evaluation, and deployment. You will work closely with researchers and engineers to bridge cutting-edge AI research with scalable, real-world applications. What will you do: Design, build, and deploy AI-powered agents that utilize LLMs for reasoning, retrieval, and action-based workflows. Implement intelligent evaluation and feedback loops to measure model performance and continuously improve AI-driven learning experiences. Develop scalable AI pipelines and AI Ops workflows to accelerate research-to-production cycles. Work with prompt engineering, fine-tuning, LLM orchestration frameworks, and model evaluation techniques to refine conversational experiences. Collaborate cross-functionally with researchers, engineers, and product teams to integrate AI seamlessly into ELSAs platform. What you will need: Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, OpenAI function calling, or similar). Experience building agent-based AI systems that integrate multiple tools, APIs, or retrieval methods. Strong experience deploying and iterating on AI applications, focusing on user impact rather than just model performance. Proficiency in NLP, LLMs, and generative AI frameworks, with experience in both open-source tools like PyTorch, TensorFlow, Hugging Face, and transformer-based models, as well as closed-source models and platforms such as OpenAI, Anthropic, Gemini, DeepSeek, LangChain, and LangSmith. Strong software engineering background, including experience with APIs, microservices, containerization (Docker, Kubernetes), and cloud services. Nice to haves: Experience with multi-step reasoning models and structured inference techniques (Chain-of-Thought, Tree-of-Thoughts, Graph-based reasoning). Hands-on experience with AI agent architectures, including self-improving, multi-agent collaboration tools like DSPy, CrewAI, or Microsoft Autogen. Familiarity with memory-augmented AI, knowledge distillation techniques, and continual learning approaches for evolving AI models over time. Strong knowledge of parameter-efficient fine-tuning (LoRA, QLoRA, PEFT) and model compression for efficient deployment. Understanding of integrating LLMs with external APIs and structured retrieval systems, improving AI accuracy with hybrid search techniques. Why will you love working here? Experience the true spirit of a fast-growing and well-funded Silicon Valley startup. Fun energetic team; international and collaborative culture. Opportunities to grow professionally and play a critical role in shaping the next stage of the companys growth. How to apply: If you are ready to take on this exciting challenge and drive growth for ELSA, please submit your resume and a cover letter detailing your relevant experience and why you are the ideal candidate for this role to . Originally posted on Himalayas

AI Engineer

Workday

San Francisco Bay Area, United States

What the job involves As an AI Engineer in Agent Factory, you will develop and integrate the intelligent feature layers behind Workday’s next generation of AI agents. While our ML Engineers focus on building, training, and optimizing foundational algorithms, your mission is intelligence orchestration and product delivery—connecting the brain to the product Working within a collaborative, cross-functional pod, you’ll implement how pre-trained foundational models (LLMs, vision APIs, etc.) power functional, user-facing enterprise software. You will be hands-on with building Retrieval-Augmented Generation (RAG) pipelines, managing orchestration frameworks, and continuous prompt engineering This role sits at the intersection of AI application building and software engineering: you will work closely with senior engineers, product managers, and designers to turn cutting-edge agentic workflows into highly responsive, reliable, and user-centric features embedded directly into the Workday stack Requirements 5+ years of professional software engineering experience, with a solid track record of developing, testing, and deploying production code 1+ years of professional experience (or a strong, demonstrable portfolio of applied project work) working with Large Language Models (LLMs), foundational models, or modern AI APIs Demonstrated experience working with AI orchestration concepts (e.g., LangChain, LlamaIndex, or similar tooling) and a strong foundation in prompt engineering to build functional LLM-powered features 2+ years of hands-on experience with API integration, backend application development, and managing data pipelines 2+ years of experience working with core development languages (such as Python) and handling modern software engineering workflows (CI/CD, testing frameworks, and version control) Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or an equivalent technical field Product & Application Focus: A strong interest in user experience and a passion for applying AI capabilities to solve practical, real-world customer problems Hands-on Orchestration: Familiarity with AI orchestration concepts, vector databases, semantic search, and prompt optimization techniques Data Fluency: Experienced in handling data exploration, transformation, and integrating varied data sources to contextually ground AI outputs Agile Collaboration: Proven ability to thrive in a team environment, collaborating closely with software developers, product managers, and UX designers Curiosity & Growth Mindset: Eagerness to stay up to date with the rapid advancements in generative AI, autonomous agents, and LLM application design

Required Skills & Experience - 2-3 years of professional software development experience, including experience delivering production-grade SaaS applications. - Strong full-stack development experience using Node.js, TypeScript, and React, with the ability to contribute across both backend and frontend systems from day one. - Hands-on experience building scalable backend services, RESTful APIs, and microservices using Node.js and TypeScript. - Advanced React experience, including hooks, modern state management, and frontend performance optimization. - Demonstrated experience integrating AI or LLM APIs into production applications, intelligent workflows, or customer-facing products. - Experience designing applications using relational and/or NoSQL databases such as PostgreSQL, MySQL, or MongoDB. - Previous technical leadership experience, including leading architecture decisions, conducting code reviews, mentoring engineers, and collaborating with product and design teams. - Experience working for an AI-focused company or a portfolio of deployed AI applications, projects, or GitHub contributions. Nice to Have Skills & Experience - Experience implementing AI guardrails, prompt orchestration, caching, rate limiting, and model evaluation frameworks. - Experience with GraphQL, event-driven architecture, or distributed microservices. - Experience with AWS, Azure, or GCP, along with Docker and CI/CD pipelines. - Experience leading engineering teams that include both U.S.-based and offshore developers. Job Description Day-to-Day: Insight Global is seeking a Lead Full-Stack Engineer to help design, build, and deploy next-generation intelligent applications for a startup that is currently in Stealth Mode. This individual will serve as a hands-on technical lead for a small engineering team consisting of U.S.-based and offshore developers. The Lead Full-Stack Engineer will build and maintain scalable Node.js and TypeScript backend services, develop modern React-based user interfaces, and integrate AI capabilities through LLM APIs, intelligent agents, and automated workflows. This person will help make architectural decisions across the full technology stack while ensuring applications remain secure, reliable, performant, and scalable. Additional responsibilities will include optimizing frontend and backend performance, supporting database design, conducting code reviews, improving automated testing practices, and mentoring junior and mid-level engineers. This individual will work closely with product managers, designers, and business stakeholders to translate product requirements into practical technical solutions. The ideal candidate is comfortable operating in a fast-paced and highly iterative environment, can take ownership of complex technical initiatives, and can clearly communicate technical and AI concepts to both engineering and non-technical stakeholders. The underlying role also emphasizes modular architecture, automated testing, technical documentation, and mentorship. Compensation: Compensation ranges from $170,000 to $210,000 annually, depending on experience, qualifications, and location. Equity is also available. We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to Human Resources Request Form. The EEOC "Know Your Rights" Poster is available [here](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf).

AI Engineer Role OverviewWe are seeking an AI Engineer / Architect for a high-impact platform initiative focused on modernizing internal systems and accelerating engineering productivity through AI. This individual will operate in a player/coach capacity, owning architecture decisions while remaining hands-on in implementation. The ideal candidate has an AI-first mindset with experience leveraging LLMs and AI tooling to design, build, and scale systems. Key ResponsibilitiesLead architecture and development of enterprise platforms, including authorization and asset management systems.Act as a technical lead for multiple engineers, providing guidance, oversight, and code review.Architect solutions, contribute hands-on to development, and delegate delivery across team members.Drive daily communication with leadership, including stand-ups and status updates.Leverage LLMs and AI development tools to accelerate engineering velocity and solution design.Translate technical concepts for non-engineering stakeholders and leadership.Support long-term technical planning and roadmap execution.Required QualificationsExperience as a Lead Engineer or Architect in enterprise environments.Hands-on experience with LLMs and AI/ML tooling, such as LLM SDKs and AI-assisted development.Proven ability to architect and implement scalable systems.Demonstrated capacity to lead and mentor engineers while operating in a player/coach role.Experience driving code reviews, technical decision-making, and cross-team collaboration.Communication skills to engage both technical and non-technical stakeholders.Preferred QualificationsBackground in Java / Spring Boot environments.Experience architecting and building authorization platforms or asset management systems.Ability to architect systems and implement them end-to-end.Experience working in AI-first engineering environments or transitioning teams toward AI-driven development.Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing® in Talent Satisfaction in the United States and Great Place to Work® in the United Kingdom and Mexico.Everforth Apex uses a virtual recruiter as part of the application process. Click here for more details. By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Everforth Apex and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at https://www.apexsystems.com/privacy-policyEverforth Apex Benefits Overview: Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our ‘Welcome Packet’ as well, which an Everforth Apex team member can provide.Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.If you require an accommodation under the Americans with Disabilities Act to participate in an interview with a virtual recruiter or to use our website for a search or application, please contact our Benefits Department at accommodations@apexsystems.com or 804-523-8228. Please note that this contact information is strictly to be used for medical ADA accommodations and that no other inquiries will be answered.UnitedHealthcare creates and publishes the Transparency in Coverage Machine-Readable Files on behalf of Everforth Apex Systems.

AI Engineer

CoreWeave

San Francisco Bay Area, United States

What the job involves The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world This team builds the tooling that engineers rely on to identify and diagnose customer issues faster We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping This is a full-ownership role: you ship your own services and stay responsible for how they behave in production You'll work closely with the engineers who use what you build Design and build AI agents that investigate and act on real customer issues Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems Determine the optimal balance between AI and deterministic logic Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next Deploy and operate your own services on Kubernetes, including supporting them when something breaks Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way Requirements 3+ years of professional software engineering experience, with strong proficiency in Go or Python Experience taking an AI application from prototype to production use and supporting it afterward Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom Experience with observability for LLM applications, including tracing, cost, and latency Working knowledge of Kubernetes and experience deploying services through CI/CD Experience integrating with third party APIs, including authentication and secrets handling (Desirable) Experience building conversational or chat-based interfaces for internal users (Desirable) A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system (Desirable) Experience testing both deterministic and non-deterministic systems (Desirable) Experience with fine-tuning or building training datasets from production data (Desirable) Open source contributions to AI tooling or agent frameworks Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency