Software Product Reliability Engineer Jobs

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

Join the engineering teams that bring OpenAI’s ideas safely to the world! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic-testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU, storage, GPU, and network lifecycle management to drive efficiency, accountability and dynamic optimization of our resources. Implement fault-tolerant and resilient design

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automation to reduce manual work

About the Role Dots is looking for a Backend Engineer to build the systems that power our product. You’ll work closely with product, design, and engineering to turn ideas into reliable services and deliver features from design through production. In this role, you will: Design, build, and maintain backend services and APIs. Develop data models and improve database performance. Build integrations with third-party services. Improve system reliability, security, and observability. Write tested, maintainable code and participate in code reviews. Investigate production issues and address their root causes. Help shape technical decisions as the product grows. You might thrive in this role if you have: Experience building and operating backend applications in production. Strong proficiency in a backend programming language. Solid understanding of API design, relational databases, and data modeling. Experience with cloud infrastructure, automated testing, and deployment workflows. Ability to balance speed with quality and make practical technical decisions. Clear communication and a collaborative approach to solving problems. Nice to have: Experience with distributed systems, background jobs, and event-driven architectures. Familiarity with caching, queues, and performance optimization. Experience working on a small team or an early-stage product. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national

Zoox is developing state-of-the-art autonomous vehicle software for our purpose-built vehicle. We believe that developing the end-to-end product will not only help us scale our services but will also result in a superior customer experience. In this role, you will build and operate the continuous deployment platform that carries changes from merge to production. You will own both the platform and its adoption: building the paved path that every production change travels on and working directly with application teams to move them onto it. We are looking for an engineer who is opinionated about what the right path looks like, who has the judgment to decide where to hold the line and where to leave room for the team, and who has a strong bias toward execution. This is a critical role to remove friction from our release process, improve the deployment experience for everyone in the software organization, and ultimately help us scale our autonomous vehicle fleet to more riders and more cities. In this role, you will: Own the reliability and operational excellence of our deployment platform Build and own the paved path for continuous delivery, and own the safety net that makes the platform trustworthy Work cross-functionally with application teams and SRE to move services onto the paved path, turning recurring friction into platform capability rather than one-off support Set the technical bar for how code is shipped safely to production, and mentor the engineers around you Qualifications 5+ years of software engineering experience, including significant experience in platform, infrastructure, or production operations Hands-on experience with a continuous deployment system in a large organization, Harness preferred; ArgoCD, Spinnaker or other relevant systems Hands-on experience with Kubernetes and container-based deployments Expertise wit

The MongoDB Customer Observability Team is a diverse group of contributors working together to help our users manage MongoDB at global scale. The team is responsible for MongoDB Atlas: our database-as-a-service offering and fastest-growing product, which allows users to deploy globally distributed MongoDB clusters in just minutes. We're seeking an SE3 to join our team to tackle exciting challenges within the Observability space. You'll contribute to developing tools and platforms that help our users understand the health and performance of their MongoDB deployments. This includes collecting metrics, monitoring slow queries, and offering actionable insights such as index and schema suggestions that improve the speed, efficiency, and overall reliability of their databases. This role provides a unique opportunity to drive engineering excellence across both dimensions of observability, leveraging technologies being developed within the Customer Observability group and contributing directly to the success of our customers and our product teams. If you're passionate about large-scale systems, digging deep into telemetry data, and building tools that make a real impact both internally and externally, we’d love to have you on board! We are looking to speak to candidates who are based in Dublin for our hybrid working model. We're looking for someone who Enjoys collaboration and being part of a team Is approachable, curious, and intellectually honest Is a backend engineer with a willingness to take on frontend tasks or a full-stack developer with a bias towards backend Has written backend systems in a compiled language (Java, C#, Go, etc.) Has experience with the design and architecture of a modern, scalable web application Is familiar with debugging and troubleshooting production issues Strong understanding of algorithms, data structures and their time and space complexity Nice to Haves Experience developing and writing code observability tools Previous work in T

About the Team Our Cyber team builds AI systems and products that help trusted defenders understand and respond to cyber threats while improving the safety and reliability of frontier models in security-sensitive settings. The team works across product engineering, model training, evaluations, safeguards, and deployment to make advanced cyber capabilities useful to defenders and responsibly managed. We collaborate closely with Safety/Preparedness, Research, Security, Legal, Communications, GTM, and external partners across OpenAI’s broader cyber work. About the Role We’re looking for research and software engineers to join Codex Cyber. You’ll help define and ship security products, work with trusted defenders and customers, shape model training and access patterns, and build research and evaluation systems for assessing cyber capabilities, validating safeguards, and improving training data. This role is hands-on and cross-functional, connecting product launches, model development, safety work, and real-world security use cases. In this role, you will: Help define and execute the technical roadmap for Codex Cyber’s security products, including evaluations, safeguards, trusted-defender workflows, and deployment decisions. Work with trusted defenders, customers, and partner teams to understand cyber use cases, evaluate risk, and turn feedback into product and research priorities. Shape cyber-specific model training and access patterns, including data, evaluations, validation, and deployment criteria. Build and validate systems for measuring cyber capabilities, monitoring misuse risk, and proving safeguards work in practice. Collaborate with Safety/Preparedness, Research, Security, Legal, Communications, Go-to-Market, and external partners on company-wide cyber priorities. Translate frontier cyber research into launch-ready tools, operational playbooks, and durable infrastructure for Codex and security products. You might thrive in this role if you: Enjoy 0 -> 1 envi

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

About the Role At Jumio, the Software Development Engineer IV - QA (SDE-IV, QA) is a senior technical role focused on ensuring the quality, performance, and reliability of highly scalable web portals and distributed backend systems. Our platform spans multiple Java Spring Boot microservices and customer-facing web portals , deployed across AWS ECS, EKS, and Lambda , and integrated through event-driven messaging using SNS/SQS . In this role you will design and drive the test automation strategy for both UI (Playwright) and API/service layers, set the quality bar for the team, and act as a force multiplier — mentoring other engineers and embedding quality earlier in the development lifecycle. You will work closely with development, product, and DevOps teams to ensure our products meet the highest standards of quality, scalability, and security. This is a hands-on senior IC role: you will write code, but you will also influence architecture, own cross-service test strategy, and make build-vs-buy decisions for testing tooling. T-Shaped Engineering Expectation As part of Jumio's engineering culture, you will adopt a T-shaped engineering approach. Beyond deep expertise in test automation and quality engineering, you will contribute across the development lifecycle — understanding software architecture, participating in design and API-contract discussions, reviewing application code, and ensuring our distributed systems are testable, observable, and resilient by design. Role Value This role is critical to ensuring the reliability, scalability, and security of Jumio's products. By architecting and maintaining automated testing frameworks across web, API, and event-driven layers, you will enable faster, higher-confidence releases and reduce production risk in a complex microservices environment. What You'll Do Test Architecture & Strategy Define and own the end-to-end automated test strategy across web portals and backend microservices, balancing UI, API, contract, integ

The Team + The Role Our Engineering Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early. You will implement guardrails that hold up under real-world usage and load. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems are observable, performant, and production-ready. Full-stack delivery: Contribute across the stack when needed to g

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Production Engineering team focuses on end-to-end reliability, durability, scalability, and performance of Figma products and services. We’re looking for an experienced Engineer to scale and drive the initiatives and programs that support Figma’s production engineering efforts, allowing our product teams to rapidly deliver new features. This is a critical part of success for both our ability to build new products and features, support the growth of our user base, and enable innovation for all engineering (infrastructure and product teams, alike). We’re looking for a generalist with a strong grasp of Computer Science fundamentals. The ideal candidate will have experience building and running complex large scale services. Additionally, they will have a passion for building tools that simplify operating large-scale infrastructure and for improving the operational maturity of Figma. What you'll do at Figma: Work closely with the engineering team to define standard methodologies and goals around reliability, durability, scalability, and performance Address common operational challenges through better telemetry and by building tools / services Debug production issues across services and levels of the stack Participate in design reviews and production reviews for new features, products or infrastructure components Plan for the growth of Figma’s infrastructure Operate and maintain AWS Infrastructure We’d love to hear from you if you have: Have 5+ years of experience operating infrastruct

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Production Engineering team focuses on end-to-end reliability, durability, scalability, and performance of Figma products and services. We’re looking for an experienced Engineer to scale and drive the initiatives and programs that support Figma’s production engineering efforts, allowing our product teams to rapidly deliver new features. This is a critical part of success for both our ability to build new products and features, support the growth of our user base, and enable innovation for all engineering (infrastructure and product teams, alike). We’re looking for a generalist with a strong grasp of Computer Science fundamentals. The ideal candidate will have experience building and running complex large scale services. Additionally, they will have a passion for building tools that simplify operating large-scale infrastructure and for improving the operational maturity of Figma. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Work closely with the engineering team to define standard methodologies and goals around reliability, durability, scalability, and performance Address common operational challenges through better telemetry and by building tools / services Debug production issues across services and levels of the stack Participate in design reviews and production reviews for new features, products or infrastructure components Plan for the growth of Figma’s infrastructure Operate and maintain AWS Infr

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a