Senior Principal Software Engineer (Tools & Platforms, Cortex)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves We are seeking a Senior Principal Software Engineer who is first and foremost a software craftsman with a passion for building innovative tools, platforms, and infrastructure that enable engineering excellence at scale This is a highly influential technical leadership role for an engineer who combines deep software engineering expertise with strategic thinking and a proven ability to shape technology direction across multiple teams and organizations The ideal candidate possesses extensive experience building large-scale distributed systems, developer platforms, and cloud-native infrastructure while serving as a trusted technical advisor and mentor You will define architectural vision, establish engineering standards, drive cross-functional technical initiatives, and lead the development of solutions that improve developer productivity, operational excellence, and platform reliability If you thrive on solving complex technical challenges, influencing engineering strategy, and building scalable systems that empower engineering, platform engineering, SRE, and R&D teams, we'd love to hear from you Define and drive the long-term technical vision and architecture for developer platforms, infrastructure, and engineering tooling across multiple organizations Architect, design, and implement resilient, secure, scalable, and highly available infrastructure and platform solutions that support enterprise-scale engineering operations Write high-quality platform and infrastructure software while setting the engineering standard for maintainability, performance, security, and operational excellence Lead the design and implementation of highly complex, business-critical systems and platform capabilities with organization-wide impact Serve as the primary technical leader for large cross-functional initiatives, aligning engineering teams on architecture, technology strategy, and implementation approaches Lead architecture reviews and technical design discussions, driving consensus and ensuring adherence to engineering best practices and long-term architectural principles Establish engineering standards, reusable frameworks, and reference architectures that improve software quality, developer productivity, and platform consistency Provide expert-level code reviews and technical mentorship, raising the engineering bar across teams through guidance on design, testing, performance, security, and maintainability Drive modernization initiatives involving cloud-native technologies, Kubernetes, distributed systems, observability, automation, and platform engineering Lead incident response and complex production troubleshooting efforts, identifying systemic improvements that enhance platform reliability and operational efficiency Champion engineering excellence by continuously improving software delivery practices through CI/CD, infrastructure automation, and developer experience initiatives Mentor and influence Principal, Senior, and Staff Engineers while fostering technical growth, innovation, and a culture of engineering excellence across the organization Requirements Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience 9+ years of hands-on experience designing, building, and operating large-scale distributed systems, cloud infrastructure, networking, storage, and compute platforms 9+ years of deep expertise with one or more major cloud providers (AWS, Microsoft Azure, or Google Cloud) and modern cloud-native architectures 9+ years of extensive experience developing, deploying, and operating microservices on Kubernetes using modern cloud-native technologies 7+ years of extensive hands-on programming skills in Python and/or GO Demonstrated expertise in system architecture, scalability, reliability, performance optimization, security, observability, and operational excellence 7+ years of Strong experience with infrastructure as code, CI/CD automation, platform engineering, and developer productivity tooling Expert knowledge of software quality practices, code health, testing strategies, performance analysis, diagnostics, debugging, and production support (Desirable) Proven track record of leading enterprise-scale technical initiatives, influencing architecture across multiple engineering organizations, and driving engineering strategy without direct organizational authority (Desirable) Strong communication and collaboration skills, with the ability to effectively influence executive leadership, architects, and engineering teams across the organization

Staff Software Engineer (AI Software Integration, Prisma AIRS)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves Join our team as a Backend AI Software Integration Engineer building a multi-tenant GenAI Security Platform that enables enterprises to benchmark, red-team, and secure LLMs and agentic workflow In this core engineering role, you will focus predominantly on backend software development in Python—building middleware APIs, data ingestion endpoints, and integration hooks to embed Palo Alto Networks Prisma AIRS across enterprise AI pipelines and partner architectures Backend Software & API Engineering: Design, build, and maintain high-performance, asynchronous REST/gRPC microservices, background job workers, and database schemas in Python AI Ingestion & Integration Hooks: Develop clean API endpoints, webhook receivers, and data ingestion hooks to collect, route, and inspect LLM prompts, context payloads, and agent execution logs AI Gateways & Agent Workflows: Build middleware logic and AI Gateway integrations connecting model providers and agentic frameworks (LangChain, LlamaIndex, MCP) with inline security controls, policy enforcement, and fallback routing Solution Architecture & Blueprints: Author technical architecture diagrams and integration blueprints documenting insertion points for the Prisma AIRS portfolio (Model, Red Teaming, Runtime, and Agent Security) within cloud and hybrid environments Automated Red-Teaming & API Exposure: Engineer programmatic execution pipelines for automated LLM probing (jailbreaks, prompt injections) and expose structured API endpoints to serve telemetry data to frontend dashboards and SIEM tools Technical Onboarding: Review partner software architecture and provide documentation or SDKs to speed up integration timeline Travel: This role may require travel Requirements Experience: 4+ years in Software Engineering or Systems Integration with a primary emphasis on backend development and cloud security Backend Python Depth: Production-level mastery of Python for asynchronous backend services, API frameworks (FastAPI, Flask, or gRPC), and microservice architectures Core Software & API Development: Experience developing, debugging, and integrating enterprise APIs (REST, gRPC, WebSockets) and API gateways (e.g., Envoy, Kong) Data Transformation: Experience writing code to map, translate, and standardize mismatched data formats between systems System Orchestration: Experience building robust middleware, webhooks, and retry logic to handle high-volume sync traffic and system failures AI Stack Integration: Practical experience integrating LLM APIs, vector storage, and agentic protocols/frameworks (LangChain, LlamaIndex, MCP) via backend middleware Architecture & Security: Proven ability to create technical architecture blueprints (e.g., Lucidchart) and secure AI workloads against prompt injection and model vulnerabilities. Rapid mastery of Prisma AIRS Testing & Quality Assurance: Experience using testing frameworks (e.g., PyTest, unittest) and robust evaluation workflows for distributed systems Communication: Excellent customer focus, collaboration and communication skills Education: BS/MS Computer Science, Computer Engineering, or related technical field or equivalent or equivalent military experience (Desirable) Asynchronous Systems: Strong background in distributed task queues (e.g., Celery, Redis, RabbitMQ) and event-driven backend architectures (Desirable) AI Security Expertise: Hands-on experience with automated AI red teaming, prompt defense tools, and securing Model Context Protocol (MCP) server interactions (Desirable) Ecosystem Familiarity: Working knowledge of major enterprise platforms (e.g., ServiceNow, Databricks, Glean)

Principal Engineer (Capacity/Compute)

Anthropic

New York, United States

What the job involves Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment This is a pipeline role feeding four areas Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company Requirements A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction (Desirable) Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here (Desirable) Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads (Desirable) Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements (Desirable) Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers (Desirable) Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level (Desirable) Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed (Desirable) Storage efficiency, retention, and lifecycle program experience at exabyte scale Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this We encourage you to apply even if you do not believe you meet every single qualification

Staff+ Software Engineer (Platform Safety)

Anthropic

San Francisco Bay Area, United States

What the job involves Platform Safety builds the infrastructure that lets Anthropic bring its most capable models to more people, safely and securely Our systems decide both who can access our most advanced models, and what capabilities they can access, wherever Claude is available That includes identity and business verification, trusted access programs, and the core services that grant, hold and enforce model access across our products. These systems already power the Cyber Verification Program, which now includes Project Glasswing, and the Life Sciences Verification Program with further more advanced use cases in development As a Staff+ engineer, you'll help set the technical direction for this work. The foundations are live and adoption is growing quickly, so the next challenge is scale: making access a matter of configuration instead of code, making verification reusable, and giving customers a consistent experience on every surface You'll work closely with safeguards, product, design and research to turn safety policy into systems that are easy to use and enforce. You'll also take new 0 → 1 efforts from idea to delivery as new capabilities and programs emerge You'll design, build and operate the systems that decide who gets access to our most capable models. You'll build the platform that lets teams across Anthropic launch and run trusted access programs, moving access rules out of code and into data so that launching a new model or complex program is simple and scalable You'll build out our identity and business verification system (KYC/KYB) as a reusable service that any program can use, which means integrating verification vendors, protecting sensitive personal data, expanding into new regions, and building fair review and appeal paths for customers. You'll also evolve the core services behind every access decision, including the services that grant and hold access and the customer and user identity models they rely on, and keep them highly available and consistent across our own products and cloud platforms You'll shape the architecture through clear written proposals, review key designs, and mentor engineers on a growing team. You'll also share on-call, lead incident response, and support emerging new programs Requirements Have a minimum of 8 years of practical experience as a backend or platform engineer, ideally at tech lead level or equivalent, and are comfortable working across the stack when the problem calls for it Have strong product sense, and work closely with cross-functional partners, including non-engineers, to shape and execute strategy in new domains Use AI tools as a regular part of how you design, build and review software Have designed and operated production distributed systems on a critical path, where correctness, latency and availability all matter Take full ownership of your work, from design through build, deployment, operations and iteration Navigate ambiguity and make sound technical decisions independently, have set technical direction that other engineers and teams adopted, and have ideally operated in both 0 → 1 and more mature settings Care about building robust, scalable systems that other engineers and businesses love to use Care about the societal impacts of your work and Anthropic's mission to build safe, beneficial AI (Desirable) Identity, access control or authorization systems at scale (Desirable) Fraud, risk, trust and safety, or KYC/KYB systems, including working with verification vendors (Desirable) Regulated or compliance-sensitive environments, including handling sensitive personal data (Desirable) Integrating with cloud platforms or partner ecosystems such as AWS, Google Cloud and Azure Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed

Principal Software Engineer (Data Platform Prisma AIRS)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves Partner with Product Management, SRE, ML Engineering, Security Researchers, and Quality Engineering to design and deliver high-throughput data platform capabilities and streaming services Architect and build resilient, multi-source batch and streaming engines to power analytical workflows, business insights, and internal feature improvements Profile, benchmark, and tune distributed execution DAGs, state storage, and compute resources to maximize throughput, lower processing latency, and optimize cloud expenditure at scale Evangelize and implement modern software engineering best practices, including spec-driven development, comprehensive testing frameworks, and agentic coding workflows Act as a force multiplier by mentoring senior and junior engineers, conducting rigorous architectural reviews, and cultivating a culture of technical excellence across the team Requirements Bachelor's degree in Computer Science or a related field with 10+ years of relevant industry experience, or a Master's degree with 8+ years of experience Deep domain expertise in designing, building, and operating highly scalable, fault-tolerant distributed systems, with exceptional programming skills in Golang and Python Hands-on experience building backend data platform infrastructure using distributed execution engines such as Apache Beam or Apache Spark Hands-on experience architecting, building, or deploying complex agentic workflows, tool-use pipelines, or multi-agent orchestrations within data infrastructure Proven track record of profiling, benchmarking, and tuning high-throughput distributed pipelines to improve latency and resource efficiency Broad experience with cloud-native data stacks (GCP/Dataflow preferred), messaging (Pub/Sub, Kafka), storage engines (BigQuery, Iceberg), and infrastructure tooling (Kubernetes, Terraform) Demonstrated ability to drive consensus across multi-team boundaries, solve complex technical problems, and mentor senior engineering talent (Desirable) Active contributions or committer status in open-source big data projects (Apache Beam, Spark, Airflow, Iceberg, etc.)

Senior Software Engineer

Hippocratic AI

San Francisco Bay Area, United States

What the job involves Hippocratic AI's AI agents are already working inside real hospitals and health systems — this role owns the backend infrastructure that keeps them fast, reliable, and ready to scale as that footprint grows You'll architect systems built for tomorrow's volume, not just today's, working closely with data scientists, ML engineers, and product managers to turn healthcare requirements into production-grade infrastructure Architect backend systems that sustain 99.9%+ uptime for high-volume healthcare data and LLM processing as usage grows exponentially Implement monitoring that surfaces issues before they reach production AI agents Own performance and reliability improvements across backend systems in collaboration with data scientists and ML engineers Infrastructure supporting data ingestion, feature extraction, and tagging workflows Develop APIs and microservices that reduce processing time and improve responsiveness for AI model interaction and data retrieval Build infrastructure that makes ML workflows reproducible end-to-end, from data preparation through model deployment Accelerate time-to-production for new AI capabilities What Success Looks Like: Within 6-12 months, the backend systems you've built or hardened are sustaining 99.9%+ uptime under exponential growth in healthcare data and LLM traffic. New AI capabilities move from data preparation to production faster because the ML workflows and pipelines you designed are reproducible end-to-end. Your monitoring catches issues before they ever reach a live AI agent in a hospital setting Requirements Bachelor's degree in Computer Science, Computer Engineering, or a related field (Master's preferred) 4+ years of backend development experience using Python, Golang, or similar languages Experience building and maintaining multi-modal (speech, vision, text) data pipelines using Ray, Apache Airflow, or similar for distributed processing and model experimentation, including distributed computing frameworks like Spark or Hadoop Familiarity with relational database systems and RESTful APIs Basic understanding of cloud infrastructure (AWS, GCP, or similar) (Desirable) Exposure to AI/ML concepts or experience working with LLMs (Desirable) Experience working in teams that handle sensitive or regulated data (Desirable) Familiarity with gRPC, GraphQL, or similar (Desirable) Experience with real-time audio (Desirable) Exposure to DevOps concepts — CI/CD, deployment, Terraform, build systems (Desirable) Experience with data science

Software Engineer (AI Platform)

Nominal

New York, United States

What the job involves We're looking for an experienced software engineer to join our Hardware Intelligence team. This is a highly ambiguous, zero-to-one engineering role. You'll build the infrastructure, data systems, and AI capabilities that power the next generation of intelligent engineering tools Rather than implementing predefined product requirements, you'll work alongside customers and product leaders to discover what should exist, and then build it Success in this role comes from being comfortable making technical bets, rapidly prototyping new ideas, and turning uncertainty into working software Build the systems that power Hardware Intelligence, including agent infrastructure, evaluation pipelines, retrieval systems, and tooling for reasoning over engineering data Design and ship AI-powered workflows that help engineers investigate anomalies, perform root cause analysis, and understand complex hardware behavior Work across large-scale time series, telemetry, logs, and other engineering datasets to build robust, production-ready systems Prototype new approaches quickly, evaluate them with customers, and iterate based on real-world feedback Partner closely with engineers and product leaders to determine where the team should invest next Help establish engineering patterns, infrastructure, and best practices as Hardware Intelligence scales Engage directly with customers to understand how complex engineering problems are solved today and translate those workflows into product capabilities Requirements 5+ years of experience building AI or machine learning products that shipped to production Experience working with large datasets, time series data, observability platforms, data infrastructure, or machine learning systems A background in ML, data science, applied AI, or adjacent fields that gives you strong intuition for working with data-intensive systems Strong software engineering fundamentals, with experience designing scalable backend or distributed systems Experience taking products from zero-to-one, whether at a startup or inside an entrepreneurial team within a larger company Strong product instincts and curiosity about customer problems (Desirable) Experience working with telemetry, sensors, robotics, aerospace, industrial systems, autonomous systems, or other hardware domains (Desirable) Experience building agentic systems, LLM applications, retrieval pipelines, or evaluation infrastructure (Desirable) Familiarity with time series databases, observability tooling, or data platforms (Desirable) Experience supporting engineers or scientists working with large-scale operational data Prior startup founding experience or experience on an incubation/new products team

Senior Principal Engineer (Software)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves As a Senior Principal Backend Engineer in our group, you will be a key technical leader responsible for developing, innovating, and scaling the backend of our unified vulnerability and exposure management module in XSIAM. You will focus on the Cortex Platform and contribute to shared infrastructures, tackling complex problems to deliver significant value to thousands of customers. This role requires a can-do attitude and a passion for solving the most challenging cybersecurity threats Serve as an acknowledged technical leader, providing consultation and proactively collaborating across engineering teams to ensure alignment Drive the full lifecycle of projects from requirements gathering to final design and implementation, acting as a project lead or mentor Lead the alignment of planned work across the product by partnering with product management, UX design, and engineering stakeholders Utilize a big-picture perspective to identify, analyze, and provide practical solutions for complex existing and impending technical problems Design, build, and optimize highly scalable data models and queries using technologies such as MySQL, Spanner and BigQuery, focusing on the details to ensure performance Develop robust business logic and API endpoints using Python and Fast API, and build high-performance backend services using Go Proactively identify, articulate, and mitigate risks in projects to ensure smooth execution and high-quality output Mentor and empower other engineers across the department, fostering a culture of technical excellence and applied learning Requirements Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical field 14+ years of professional software engineering experience, with a focus on distributed, cloud-native application development Expert-level programming skills in Python, Go, or Java, with proven experience building large-scale distributed systems Extensive experience with cloud development, including REST APIs, databases, serverless computing, and microservices architectures Demonstrated experience as a hands-on technical lead or architect on complex software projects (Desirable) 8+ years of hands-on experience with specific cloud technologies such as BigQuery, Google Pub/Sub, or similar (Desirable) Deep understanding of public cloud design considerations, including security, global network infrastructure, and load bala

Senior Staff Software Engineer (Cortex XSOAR)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves Palo Alto Networks is seeking a Principal Backend Engineer to become a vital part of our Cortex backend engineering group, primarily focusing on the development and maintenance of our Cortex products, including Cortex XSOAR, Cortex XSIAM, and the new Cortex AI solution. Our team operates with high efficiency and swift decision-making processes In this role, you will design and implement robust backend services for Cortex XSOAR, a leading-edge security orchestration, automation, and response platform As a member of our dynamic team, you will also contribute to creating innovative AI-based solutions leveraging the Cortex product line, enhancing shared Cortex infrastructures and components This role is an exceptional opportunity for those eager to advance Cortex XSOAR with AI-driven capabilities and make a significant mark in the cybersecurity industry Lead full lifecycle development of backend features for Cortex XSOAR on-prem and SaaS (security orchestration platform): from requirements gathering, architecture/design, implementation, testing, deployment, through to production support and maintenance Work closely with peers across different teams and disciplines to shape solutions and integrate with other parts of the product. Working on “shared responsibility” type of products Production-oriented approach, providing real-time mitigation and solutions to production issues Engage with customers and support teams to help troubleshoot and fix issues Requirements This position requires a solid background in software engineering, with proficiency in Go and Python, and a keen interest in tackling complex technical challenges within the cybersecurity sphere We value candidates who are proactive, passionate about problem-solving, and committed to delivering substantial impact to thousands of customers Education & Experience: B.S. or M.S. degree in Computer Science, a related technical field, or equivalent practical experience 5+ years of professional software engineering experience building scalable server-side applications Programming Expertise: 4+ years of extensive, hands-on programming proficiency in Go and Python Cloud & Infrastructure: 5+ years of proven experience designing and working with distributed cloud products on major platforms (GCP, AWS, or Azure), as well as containerization and orchestration technologies (Docker, Kubernetes) Systems & Databases: Advanced proficiency in Linux/Unix operating systems (command line, networking, shell scripting) and solid experience with both RDBMS and NoSQL database technologies Distributed Computing: Strong understanding of distributed computing environments, including the implications of the CAP theorem, master election, and split-brain problems Operational Excellence: Proven experience with production troubleshooting and customer response (Desirable) Strong computer science fundamentals (e.g. understanding of lock-free data structures, bloom filters, minimal perfect hashing, consistent hashing etc) (Desirable) Hands-on experience with SQL/NoSQL based databases (Desirable) Experience with distributed computing (understand implications of CAP theorem, master election, brain split problem)

Senior Principal Software Engineer (Cortex Platform)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves Cortex - Cortex is a world-leading cybersecurity platform that provides comprehensive security solutions to protect organizations from advanced threats Our team is responsible for developing and maintaining the core components of the Cortex platform, including the data pipeline, analytics engine, and user interface We are a fast-paced and innovative team that is passionate about building the best security products in the world As a Senior Principal Backend Engineer in our Cortex group, you will be a key technical leader responsible for developing, innovating, and scaling the backend of our industry-leading products, including Cortex XSOAR, XDR, and XSIAM You will focus on the Cortex Platform and contribute to shared infrastructures, tackling complex problems to deliver significant value to thousands of customers This role requires a can-do attitude and a passion for solving the most challenging cybersecurity threats Serve as an acknowledged technical leader, providing consultation and proactively collaborating across engineering teams to ensure alignment Drive the full lifecycle of projects from requirements gathering to final design and implementation, acting as a project lead or mentor Lead the alignment of planned work across the product by partnering with product management, UX design, and engineering stakeholders Utilize a big-picture perspective to identify, analyze, and provide practical solutions for complex existing and impending technical problems Design, build, and optimize highly scalable data models and queries using technologies such as MySQL and BigQuery, focusing on the details to ensure performance Develop robust business logic and API endpoints using Python and Flask, and build high-performance backend services using Go Proactively identify, articulate, and mitigate risks in projects to ensure smooth execution and high-quality output Mentor and empower other engineers across the department, fostering a culture of technical excellence and applied learning Requirements Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical field 14+ years of professional software engineering experience, with a focus on distributed, cloud-native application development 10+ years of software engineering experience, featuring deep expertise in Python, Go, or Java and a proven track record of architecting large-scale distributed systems Extensive experience with cloud development, including REST APIs, databases, serverless computing, and microservices architectures Demonstrated experience as a hands-on technical lead or architect on complex software projects (Desirable) 8+ years of hands-on experience with specific cloud technologies such as ElasticSearch, Google Pub/Sub, or similar (Desirable) Deep understanding of public cloud design considerations, including security, global network infrastructure, and load balancing (Desirable) Proven ability to make data-driven trade-off judgments and excellent troubleshooting skills to isolate and resolve complex issues (Desirable) Experience working in an agile environment with cross-functional teams to deliver full-stack products at scale

Senior Staff Software Engineer (Linux, C/C++, Global Protect)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves We are seeking an experienced Software Engineer to design, develop and deliver next-generation technologies within our GlobalProtect team We want passionate engineers who love to code and build great products and who bring new ideas in all facets of software development We are looking for leaders who take ownership of their areas of focus and who are driven to solve problems at every level Collaboration and teamwork are at the foundation of our culture and we need engineers who can communicate at a high level and work well with others towards achieving a common goal Lead the innovation, development, and maintenance of a secure access Prisma Access client on the Linux Platform, while spearheading the progression of the Prisma Access agent to establish it as a foundational product Collaborate with product management to craft strategic roadmaps that elevate Endpoint capabilities and ensure smooth integration with the new Prisma Access agent Design scalable system architectures, participate in team-wide initiatives, and deliver immediate resolutions to production challenges to guarantee a seamless user experience Provide mentorship and coaching to team members to foster their professional growth Integrate AI-driven technologies and frameworks into the Linux agent to optimize client performance, enhance security telemetry, and enable intelligent threat response Requirements 8+ years of experience in software development with a focus on Linux 2+ years of hands-on experience in Linux systems programming, with a deep understanding of Linux kernel internals and system-level programming ​​Familiar with multiple Linux distributions: RHEL, Ubuntu, Fedora, etc Proficiency in C/C++ programming languages, with a strong emphasis on Linux Knowledge of networking protocols and troubleshooting tools specifically on Linux platforms A team player with a can-do attitude, ready to tackle complex problems and eager to learn and grow Skilled at collaboration and effective communication across multiple teams M.S./B.S. degree in Computer Science, Electrical Engineering, or equivalent military experience

Principal Engineer Software (Threat Data Platform)

Palo Alto Networks

San Francisco Bay Area, United States

What the job involves Join the Threat Data Platform (TDP) engineering team at Palo Alto Networks, where we are redefining how threat intelligence is automated and analyzed As a Principal Software Engineer, you will build AI-driven tools that empower researchers to develop sophisticated, high-fidelity threat models Your mission is to innovate and scale our core data pipelines, ensuring seamless integration across the PANW product ecosystem to deliver critical security value to thousands of global customers Drive the end-to-end development of backend features and core components, from initial architectural design and testing to deployment and long-term maintenance Design and optimize high-throughput ETL/ELT pipelines that ingest and transform complex threat data into actionable intelligence within our data warehouse Build and maintain high-performance data warehouses and scalable APIs that serve as the backbone for PANW’s internal security researchers Partner with cross-functional stakeholders to translate complex business requirements into elegant, scalable technical solutions Champion engineering excellence through rigorous code and design reviews, contributing to the team’s architectural roadmap and best practices Requirements B.S. or M.S. in Computer Science, a related technical field, or equivalent practical software engineering experience 5+ years of hands-on experience building large-scale enterprise applications and high-availability data APIs Professional-level proficiency in Java (core backend) and a strong command of RESTful API design Proven experience with major cloud providers (GCP preferred or AWS) and their managed services Experience with Python for data manipulation, alongside expertise in Linux environments and shell scripting Strong grasp of varied database architectures, including SQL, NoSQL, Time-series, and GraphDB Experience operating within Kubernetes (K8s) environments and a solid understanding of modern CI/CD workflows (Desirable) Familiarity with building complex analytical solutions and optimizing data pipelines for machine learning or AI-driven insights (Desirable) Specific experience with GCP services such as Pub/Sub, Kafka, Dataflow, Spark, BigQuery, and BigTable (Desirable) Experience with GraphDB specifically for threat relationship mapping

Principal Software Engineer (Java)

Resource Innovations

Remote

What the job involves Resource Innovations is seeking a Principal Software Engineer to join our growing Software as a Service (SaaS) team. This is a highly influential, hands-on technical role responsible for helping shape the future architecture of our enterprise software platform You will partner with senior engineers, product leaders, and cross-functional teams to modernize a complex, business-critical platform used by leading energy organizations. You will bring proven experience designing and evolving large-scale enterprise systems, while combining a fresh architectural perspective with the deep product and domain knowledge of the existing team Define and guide the evolution of the platform architecture to improve scalability, reliability, performance, security, and maintainability Develop a practical, phased modernization approach that balances future-state architecture with current customer and business commitments Remain hands-on in the design and development of critical platform capabilities, architectural patterns, and proof-of-concept solutions Lead technical design and code reviews, establish engineering standards, and guide complex decisions across application, integration, data, and cloud architecture Partner with senior engineers and cross-functional teams to resolve complex technical challenges, mentor engineers, and translate technical direction into successful delivery Requirements The ideal candidate is both a senior architect and an accomplished software developer who can establish technical direction, translate architectural vision into practical execution, and remain actively involved in design and development We are looking for someone who is passionate about product craftsmanship, modern engineering practices, and building technology that makes a meaningful impact on the world Bachelor’s or master’s degree in computer science, Engineering, or a related field, or equivalent practical experience 15+ years of software engineering experience building complex, scalable, and reliable enterprise applications Experience operating at a Principal, Staff, Architect, or equivalent technical leadership level Proven experience designing and modernizing established enterprise software platforms Experience defining technical direction and influencing decisions across multiple engineering teams Strong hands-on development experience and the ability to translate architectural strategy into practical implementation Expert-level proficiency in Java and Spring Boot, with working knowledge of Python Deep experience with enterprise architecture, distributed systems, microservices, APIs, integration patterns, and event-driven design Strong experience with AWS, cloud-native application design, CI/CD, containers, and Kubernetes or similar platforms Experience with relational and NoSQL databases, data pipelines, messaging systems, search platforms, and observability tools Strong understanding of application security, performance, resiliency, scalability, and production-readiness practices Strong architectural judgment with the ability to balance long-term direction and pragmatic delivery Ability to influence and build alignment across teams without direct authority Excellent analytical, problem-solving, verbal, and written communication skills Collaborative approach that values and leverages the knowledge of existing team members Ability to clearly communicate technical options, tradeoffs, and risks to both technical and business stakeholders (Desirable) Modernizing mature, business-critical SaaS platforms while maintaining customer and operational continuity (Desirable) Supporting enterprise platforms with large data volumes, complex workflows, and extensive integrations (Desirable) Experience with Angular or comparable web technologies (Desirable) Familiarity with AI-assisted development tools such as GitHub Copilot, Claude, or equivalent (Desirable) Knowledge of the energy, utility, energy-efficiency, or clean-energy technology industry

Backend Engineer

Astra

Remote

What the job involves We're looking for a Backend Engineer to build and ship features across the financial systems that move real money every day You'll join a small team of experienced engineers working on our distributed microservices architecture, taking on features across payments, fraud detection, compliance, and user management from design through production This role is for an engineer who already delivers independently and is ready to take on broader scope. You'll work on larger, cross-domain problems, get real exposure to architecture decisions, and grow quickly in a domain where correctness and reliability matter Own features end to end: Design, build, test, and deploy backend features and services across payments, fraud, compliance, and user management, then run and monitor what you ship Integrate with financial partners and APIs: Build and maintain integrations with banks, card networks, and other third-party services, handling the edge cases that money movement demands Contribute to design: Write and review technical designs for your own work, participate in architecture discussions, and learn how our domain-driven, event-driven approach fits together Improve performance and reliability: Find and fix bottlenecks and failure modes across our microservices, and help raise the quality of our tests and observability Collaborate across teams: Work closely with product and compliance to turn business and regulatory requirements into working software Direct impact: You'll be a big part of a small engineering team building systems that power a growing fintech platform Complex problems: Work on sophisticated challenges that few engineers get to solve Room to grow: A path to broader scope and, over time, technical leadership as the team scales Financial innovation: Build systems that enable new financial products and services Requirements 3+ years of professional software engineering experience building production backend systems Track record of delivering features independently, from ambiguous requirements to production, with sound judgment on when to ask for help Solid foundation in algorithms, data structures, and computer science fundamentals Working experience with distributed systems, event-driven architectures, or microservices Ability and willingness to travel up to ~15% annually Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. We care more about demonstrated ability than credentials Backend development: Python 3 and web frameworks and APIs (we use Flask) Databases: Experience with SQL and NoSQL databases Cloud infrastructure: Google Cloud Platform, or similar cloud platforms Architecture patterns: Familiarity with domain-driven design, clean architecture, and CQRS is a plus (Desirable) Financial systems: Payment processing, fraud detection, or compliance systems (Desirable) Financial regulations: Familiarity with AML, KYC, PCI DSS, or similar regulations (Desirable) Banking integrations: Experience with financial APIs and money movement systems (ACH, card networks) (Desirable) Third-party integrations: Experience building and maintaining integrations with external services (Desirable) Scale and reliability: Experience with systems processing high transaction volumes We're looking for engineers who are excited by complex systems problems and have the educational background and experience to handle sophisticated challenges If you're passionate about building mission-critical financial infrastructure and want to have a direct impact on our technical direction, we'd love to hear from you

Member of Technical Staff (Traffic Infrastructure)

Fireworks AI

San Francisco Bay Area, United States

What the job involves As a Member of Technical Staff on our Traffic Infrastructure team, you will own the traffic layer behind our generative AI platform: the proxies, load balancers, service mesh, and routing systems that move every request reliably across regions and cloud providers. This is a highly technical role that calls for depth in distributed systems, cloud networking, and infrastructure, along with the judgment to balance latency, cost, and operational simplicity. You will partner closely with ML, product, and platform teams, and help set the technical direction for the team Architect and build scalable, fault-tolerant traffic and networking services, including ingress and egress, load balancing, routing, and quality-of-service controls Lead technical design discussions, mentor other engineers, and establish best practices for operating large-scale infrastructure Drive network optimization both inside and outside data centers, including cost reduction, performance tuning, and removing scaling bottlenecks Evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Envoy, Istio) to strengthen platform capabilities and reliability Own systems end to end, from design through deployment and observability, with an emphasis on high availability, disaster recovery, and operational excellence Develop and maintain comprehensive monitoring, alerting, logging, and tracing to give deep insight into system health and performance Requirements Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience) 5+ years of experience building backend or network infrastructure in cloud environments (e.g., AWS, GCP, Azure) Strong software development skills in languages such as Go, C++, Rust, Java, or Python Deep understanding of distributed systems and networking fundamentals, including performance optimization Full product lifecycle ownership, from design through implementation to production (Desirable) Master's or PhD in Computer Science or a related field (Desirable) Hands-on experience with traffic or edge engineering, service mesh, or cloud networking (e.g., Envoy, Istio, DPDK) (Desirable) Deep Kubernetes experience, including ingress, network policy, and custom controllers (Desirable) Track record of improving performance, reliability, and cost-efficiency on high-throughput systems (Desirable) Experience leading projects across teams and coaching distributed engineers

Senior Software Engineer (Payments)

GovWell

New York, United States

What the job involves Payments infrastructure for local government is a genuinely hard problem — real money, strict audit requirements, dozens of different fee types and collection methods, all running underneath workflows that can't afford to break. It's also a problem that's specific to how municipalities and counties actually operate, not something you can bolt on from a generic payments product GovWell is hiring a Payments Engineer to own this space and build it into the financial backbone the rest of the platform runs on. This isn't a feature added to an existing system — it's a domain still being defined, which means the person who takes this on will shape the core architecture, not just extend someone else's We have strong opinions about the principles that this deserves — real auditability, precision in how fees are computed, a system finance teams can actually trust — but we're looking for someone who can take that point of view, sharpen it, and build it. Because so much of this is still unwritten, you'll have more autonomy and ownership here than in almost any other role at GovWell This role reports directly to our CTO and Co-Founder, Ben Cohen Design the financial architecture GovWell runs on — the system of record for every dollar municipalities collect, refund, or hold on someone's behalf Build a real ledger from the ground up: one that's fully auditable, mathematically consistent, and trusted by finance teams without a second look Turn fee calculation into a system that computes with precision, instead of something staff track by hand or reconstruct after the fact Make partial payments, deposits, and refunds first-class citizens of the platform, not workarounds bolted on after the core system was built Own the migration from where payments live today to where they need to be — with real customers, real money, and no room for a clean-slate do-over Partner directly with the people who depend on this system being right: finance teams, municipal staff, and the engineers building the workflows this ledger will support Set the technical standard other engineers build against once this domain exists — you're not implementing someone else's design, you're establishing it Our tech stack: React TypeScript Node.js GraphQL PostgreSQL RedwoodJS AWS OpenAI API Finix (payments processing) Requirements Experience designing financial or transactional systems where correctness isn't optional — payments, billing, ledgers, or similar domains where an unbalanced number is a real problem, not a bug ticket You have real opinions about how a payments system should be architected, and you want a role where you can bring them, not just implement someone else's spec Comfortable with ambiguity at the domain-design level: this isn't "build this feature," it's "help decide what the right abstraction is," and you find that exciting rather than uncomfortable Experience with idempotency, webhooks, and payment processor integrations (Stripe, Finix, or similar) is a strong plus You think in terms of invariants and edge cases — what happens when a webhook fires twice, when a fee schedule changes mid-invoice, when a refund needs to partially reverse a payment that's already been partially paid You're excited to work with the latest AI models, both in the product and in your own development workflow You've owned a large product area end-to-end and can point to something specific you shipped and stayed accountable for Strong product instincts: you ask questions until you actually understand the customer's problem, not just the ticket description You align closely with our Core Values

Software Engineer (Knowledge Engine, Data Infrastructure)

Exa

San Francisco Bay Area, United States

What the job involves In this role, you'll build the knowledge construction pipelines: turning everything from a 100k docs/s web crawl to vendor datasets into a graph of what is true about the world, and keeping it correct as data changes This is greenfield work with a massive scope. There is no off-the-shelf system for building a model of the world from the open web, so you'll make foundational decisions, from how claims are represented and resolved to how trust is assigned and how the graph evolves over time, that everything built on top of it depends on Continuously synthesize the live web crawl, vendor deliveries and APIs, and other off-the-web sources into one typed graph: extraction that turns pages and records into ontology-shaped claims, each carrying its provenance, timestamp and confidence Bring every new source in cleanly: versioned, append-only history with schema evolution, late-arriving and corrected records, and replayable cursors, so every claim traces back to the exact delivery that produced it Decide what to trust: entity resolution across billions of records (blocking, pairwise scoring, clustering) into canonical people, companies, places and publications, then truth discovery that weighs source reliability, recency and corroboration to reconcile conflicting claims Keep that picture current and convergent: streams arrive continuously, out of order and at very different rates, so the graph is eventually consistent by design. You'll build incremental computation over change data feeds, where each update is a diff of what changed and every job is idempotent and resumable, so the graph converges to the same state however runs interleave, fail or replay, and readers only ever see committed, consistent versions Measure precision and completeness: labeled evals for extraction and resolution, per-source coverage and correctness metrics, and lineage that pinpoints which source or stage broke and why Requirements You've built and operated large-scale distributed data pipelines in production over petabytes of structured and unstructured data, with Spark over a lakehouse format (Delta Lake, Iceberg, Hudi) You understand incremental processing deeply: change data capture, idempotent writes, backfills and reprocessing Strong in Python and at least one systems language; you can read and tune Spark query plans You obsess over correctness, reliability and data quality as much as scale (Desirable) Entity resolution, record linkage, knowledge graphs or ontologies (Desirable) Information extraction or truth discovery at scale (Desirable) Lance or other columnar/vector-native formats

Staff Software Engineer (PostgreSQL Specialist)

ID.me

San Francisco Bay Area, United States

What the job involves ID.me is seeking a Staff Software Engineer (SDE5), PostgreSQL Specialist to lead the engineering, evolution, and operational excellence of our PostgreSQL-based data platform This role sits at the intersection of deep database internals and platform software engineering—focused on scaling our core relational databases (across CloudSQL, AlloyDB, and AWS RDS) and building the developer tooling, safe change deployment pipelines, and automated guardrails that protect ID.me’s mission-critical identity systems As a Staff Engineer on the Core Platform Data team, you will serve as the organization’s foremost technical authority on PostgreSQL internals, performance engineering, and safe database evolution at scale Beyond tuning queries and managing high-scale database infrastructure, you will act as a force multiplier for the entire engineering organization by designing and maintaining automated schema change pipelines, migration linters, and self-service guardrails that enable product engineers to ship database changes safely, rapidly, and without production disruption You will also lead high-stakes database engine upgrades, large-scale data migrations, and Change Data Capture (CDC) initiatives in partnership with Product Engineering, SRE, Security, and Compliance teams. This is a highly technical, hands-on role that combines deep mastery of PostgreSQL internals with strong software engineering skills to build resilient systems and developer-facing database automation Master & Optimize PostgreSQL Internals at Scale: Serve as the primary technical escalation point and subject-matter expert on PostgreSQL internals—including MVCC, vacuum/autovacuum tuning, transaction ID wraparound prevention, lock management, WAL/checkpoint behavior, buffer management, query planner/optimizer internals, and table/index bloat remediation Build Safe Change Deployment Pipelines & Developer Guardrails: Design, build, and maintain automated database schema change management pipelines (e.g., Liquibase/CI-CD workflows, automated DDL validation, lock/timeout guardrails, and pre-flight migration checks) that empower engineers across ID.me to deploy schema and data changes safely with zero downtime Lead Zero-Downtime Migrations & Engine Upgrades: Architect and execute complex, large-scale data migrations (accounting for data skew, batching, and index performance) as well as major version upgrades and platform transitions across PostgreSQL, GCP CloudSQL, AlloyDB, and AWS RDS Drive Query Performance & Schema Hygiene: Partner with engineering teams to review and optimize high-throughput queries, indexing strategies, partitioning/sharding designs, connection management, and role/permission models across operational and graph-adjacent relational workloads Engineer Database Observability & Diagnostics Tooling: Build and enhance custom PostgreSQL telemetry, statistics collection, query performance monitoring, and alerting to proactively detect lock contention, replication lag, slow queries, and capacity bottlenecks before they impact production SLAs Enable Event-Driven & CDC Architectures: Design and maintain reliable Change Data Capture (CDC), logical replication, and outbox/streaming integrations that bridge transactional PostgreSQL databases with ID.me’s broader event-driven and analytical data ecosystem Automate Governance, Security & Compliance: Build automated workflows and enforcement mechanisms for database access controls, cross-schema permissions, secret rotation, data retention/pruning, and regulatory compliance (e.g., FedRAMP, NIST 800-63, GDPR) Act as Production Stability Guardian & Multiplier: Establish and codify PostgreSQL best practices, conduct architectural and high-risk migration reviews, and mentor engineers across the company to decentralize database expertise and elevate the organization’s database engineering bar Requirements Bachelor’s or Graduate degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience) 8+ years of professional software development and data infrastructure experience, including 5+ years working deeply with PostgreSQL in high-volume production environments Deep, hands-on knowledge of PostgreSQL internals (e.g., MVCC, vacuuming, locking semantics, query execution plans, indexing structures, WAL, and replication) Strong programming proficiency in one or more backend languages such as Go, Python, Ruby, or Java, alongside expert-level SQL and PL/pgSQL (Desirable) Proven track record of building software, automation, and CI/CD pipelines for safe database schema changes, migrations, and developer guardrails.Demonstrated experience designing and operating automated database change management and schema migration frameworks (e.g., Liquibase, Flyway, custom DDL linters, or zero-downtime migration tooling) across a large engineering organization (Desirable) Extensive hands-on experience managing and upgrading managed cloud PostgreSQL platforms at scale, particularly GCP CloudSQL, Google AlloyDB, AWS RDS, or Aurora PostgreSQL (Desirable) Proven success planning and executing near-zero-downtime major PostgreSQL version upgrades and multi-terabyte table migrations or normalizations under strict availability SLAs (Desirable) Deep experience with PostgreSQL extensions, custom statistics/diagnostics tooling, logical replication, and Change Data Capture (CDC) pipelines (e.g., Debezium, pglogical, Airbyte, or Pub/Sub/Kafka integrations) (Desirable) Experience automating database infrastructure and lifecycle management using Terraform, Kubernetes, or Helm (Desirable) Strong understanding of data security, encryption, role-based access control, and compliance requirements in regulated environments (e.g., FedRAMP, NIST, GDPR) (Desirable) Fluency with AI-assisted engineering tools and workflows to accelerate tooling development, query analysis, and migration validation (Desirable) Track record of acting as a force multiplier—turning tribal database knowledge into self-service tools, documentation, and paved paths for other engineers

Staff Full Stack Software Engineer (UI Tooling)

Airbnb

Remote

What the job involves As a Staff Software Engineer on the UI Tooling team, you will lead our prototyping and rapid deployment platform, Kyber. You will drive implementation, maintenance, and scaling of a system that supports thousands of internal projects and users and enables non-technical builders to express ideas across all of our product surface areas You will own the strategy and execution across 3 key areas: Rebuild Kyber onto our next-generation cloud platforms Evolve Kyber capabilities to support product development process Integrate Kyber into our ecosystem supporting prototyping workflows Setting technical direction for the Kyber platform, making architectural decisions for the systems that enable rapid deployment of internal applications and product feature prototypes Write and review code hands-on and with AI coding agents, establishing and demonstrating standards for quality, availability and system health across the platform Partner with Infrastructure, Product, Security, and Design to translate cross-organizational objectives into platform capabilities Advance the capabilities for Product Managers, Designers, and other non-technical builders to build rich product feature prototypes that translate to features in our production applications Mentor engineers and act as a force multiplier, leveling up the team through design reviews, technical guidance, and a collaborative, inclusive culture Requirements 9+ years of industry experience, ideally within fast-paced environments, with a track record of delivering large-scale service oriented systems Broad full-stack engineering capability, with the confidence to work across backend, frontend, mobile, APIs and system architecture as technical challenges require Proven experience building customer-facing products from zero to one, contributing to product definition, technical architecture, development and launch End-to-end product ownership, with experience iterating on launched products, responding to customer feedback and improving adoption, usability and business outcomes Strong architectural design skills, including high-scale distributed services, well-designed APIs, data pipelines, efficient algorithms and reliable integrations Sound technical judgment, with the ability to balance speed of delivery, experimentation, scalability and long-term engineering quality A product-first engineering mindset, with an understanding that technical decisions are in service of the products we provide to our customers Strong communication and collaboration skills, with experience driving initiatives that span across teams, departments and leadership

Senior Frontend Software Engineer (Consumer, Payments)

Coinbase

Remote

What the job involves We're hiring a Senior Software Engineer, Frontend to join the Consumer Payments team within the Consumer Product Group. This team owns the infrastructure, experiences, and controls that power how millions of users send, receive, and move crypto on Coinbase You'll own critical user journeys across web and mobile, building fast, reliable, and delightful payment flows while mentoring junior engineers and driving down customer friction at scale Own end-to-end frontend development for core crypto money movement experiences, including send, receive, and transaction status tracking across web and mobile Drive measurable improvements in CUJ latency, availability, and SLOs for the payment flows you own Build new user-facing features - such as contact management systems and real-time transaction status trackers Partner with product, design, and backend engineering to scope, prioritize, and ship projects that reduce CX contact rates and improve the customer experience Identify and resolve frontend performance bottlenecks across payment flows, reducing end-to-end latency and improving reliability for millions of users Requirements 5+ years of software engineering experience with deep expertise in React and React Native Proven track record of shipping consumer-facing products end-to-end in a high-scale environment, with a focus on performance, reliability, and user experience Experience owning SLOs and driving measurable improvements in latency and availability for user-facing flows Demonstrated ability to mentor junior engineers and operate as a senior technical voice on a team of mixed levels Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality