Software Infrastructure Kubernetes Engineer in London

About the Team The Applications Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. 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 The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change 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

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About the Role We're seeking a Senior/Staff Engineer to build and maintain the automation infrastructure that powers the development cycles of our North platform. This engineer will design and implement robust automation systems that enable engineers to efficiently test and validate changes across diverse environments and configurations. This role sits at the intersection of infrastructure and standards. You'll build the systems, frameworks, and culture that allow the rest of engineering to own quality themselves; improving and extending our testing platform by creating the infrastructure that allows engineers to write and execute tests, and enable every engineering team to ship with more confidence. Key Responsibilities Design and implement automation pipelines that support comprehensive testing across multiple environments with varying feature flags and realistic customer data profiles Create intelligent testing agents that simulate real user behavior to validate different configuration combinations Develop and maintain GitHub workflows and actions to automate testing, deployment, and validation processes Manage and optimize H

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We’re looking for Forward Deployed Infrastructure Engineers who can help us build, operate, and maintain high-performance, scalable, and reliable services for Palantir platforms, products, and deployments. You'll get to use your creativity to develop novel solutions to evolving challenges and automate processes wherever possible, using whichever tools are best for the job including industry-leading LLM and AI technology! As a Forward Deployed Infrastructure Engineer, every day is different! You will be developing software and providing high-quality support for software systems that are critical to solving our government’s greatest challenges. We strongly believe in engineering teams being responsible for the operations of their services in production. As such, you’ll work closely with forward deployed teams and product teams to participate in sensible, scalable, systems design and share responsibility with them in diagnosing, resolving, and preventing production issues.

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. We develop the systems and tools that make it possible to introduce new models, manage production deployments, respond to operational issues, and use infrastructure effectively at scale. Our work spans distributed systems, platform engineering, infrastructure automation, and developer experience. We partner closely with research, infrastructure, and product teams to make model deployment more reliable, more efficient, and easier to manage. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will design and develop systems that support the model lifecycle in production, including deployment orchestration, configuration management, operational automation, reliability, and capacity management. You will help transform complex operational processes into scalable platform capabilities that enable teams across OpenAI to deploy and manage models with greater confidence and less manual effort. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build and evolve the platform used to deploy, configure, and manage models across ChatGPT. Develop systems for deployment orchestration, model rollouts, operational visibility, and production readiness. Create abstractions and tooling that simplify complex infrastructure and improve the developer experience. Automate operational workflows, including incident detection, diagnosis, mitigation, and recovery. Improve the reliability, scalability, and efficiency of model deployments and the infrastructure that supports them. Build systems that support capacity planning, resource allocation, and infrastructure utilization. Partner with research, infrastructure, and product engineering teams to identify common chal

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are seeking a talented Software Engineer to join our X Money team, focused on building a revolutionary global payment network that will serve over 600 million users and rival the world’s largest financial institutions. In this role, you will specialize in backend development, designing and optimizing robust microservices to ensure scalability, security, and reliability. You will support full-stack efforts, collaborate with cross-functional teams on payments, fraud detection, and compliance initiatives, and contribute to the creation of a high-scale financial products platform. This is an opportunity to work on greenfield projects in a fast-paced, startup-like environment, driving innovation at the intersection of AI and finance. RESPONSIBILITIES: Develop backend services, APIs, and data models to support high-volume, multi-user environments. Work with iOS, Android & Web client engineers to ship products. Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms. Build and maintain fullstack features, including user dashboards, personalized experiences, content delivery, interactive tools, assessments, and real-time analytics. Le

ABOUT THE ROLE We are a leading streaming global fitness content company with studios around the world including London, revolutionizing the way people access and engage with fitness workouts. Our platform offers a wide range of interactive, live and on-demand fitness content that caters to users of all fitness levels, empowering them to stay fit and healthy from the comfort of their homes. As the Senior Manager of Broadcast Engineering, you will play a pivotal role in our mission to deliver high-quality, seamless, and engaging fitness content to our global audience. You will lead the Broadcast Engineering team based in London, ensuring the smooth operation and optimization of our broadcast infrastructure, content delivery systems, and broadcast equipment. This position reports to the Director of Global Production Technology. YOUR DAILY IMPACT AT PELOTON Oversee and guide the Broadcast Engineering team in designing, implementing, and maintaining an efficient and reliable broadcast studio facility to deliver the best member experience possible Collaborate with global broadcast engineering leads to maintain parity and system wide connectivity between facilities Manage the procurement, installation, and maintenance of all broadcast equipment, ensuring their proper functioning and readiness for live and on-demand fitness classes Collaborate with cross-functional teams, including Content Production Operations, IT, and Product, to streamline content workflows, improve efficiency, and enhance the overall broadcast transmission process Stay up-to-date with the latest trends, advancements, and emerging technologies in broadcast engineering and streaming to propose and implement cutting-edge solutions Lead the team in promptly addressing technical issues and incidents, minimizing downtime and disruptions to the streaming service Mentor and guide the Broadcast Engineering team members, fostering a culture of learning, growth, and innovation YO

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: The Sandbox service team at SpaceXAI builds and maintains a secure, scalable system that gives our models safe, controlled access to computational environments. This infrastructure powers critical workloads across training and product, enabling models to run code, build software, interact with tools, and even control applications with user interfaces. We provision containers and virtual machines on large-scale clusters, granting models interactive control over these remote environments. Our work spans the full stack: from orchestrating massive jobs and resource scheduling at the cluster level, to fine-tuning filesystem performance on nodes. The Sandbox service enables Grok to safely run and test code in real-time for user queries, and supports reinforcement learning in training, where models interactively explore tools ranging from compilers to productivity apps. BASIC QUALIFICATIONS: Expert knowledge of Rust, C++ or Go Familiarity with Python Deep experience with either Linux or Windows systems (familiarity with both is a strong plus) Experience with virtualisation and containerisation technologies (e.g., cgroups, KVM, gVisor, QEMU) Solid knowledge of the networking stack COMPENSATION AND BENEFITS: £107,000 -

About the Team Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. About the Role As a Training Runtime: Process Management Engineer , you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust , building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re loo

About the Team OpenAI’s Network Security team designs and operates the secure, reliable connectivity behind our offices, labs, campuses, cloud environments, people, and devices. We combine strong network fundamentals with automation, observability, and close partnership across IT, Security, Research, Applied, and business teams. About the Role As a Network Engineer, you will design, operate, troubleshoot, and automate secure, reliable networks across offices, labs, cloud connectivity, and production services. You will balance strategic platform work—architecture, standards, roadmaps, lifecycle planning, and automation—with responsive operations such as incidents, escalations, break/fix, and time-sensitive delivery. We’re looking for broad network engineers who meet users where they are, lead with curiosity, own outcomes end-to-end, move with urgency grounded in security, and iterate with purpose. You will turn operational signals and recurring reactive work into durable systems and standards. In this role, you will: End-to-end ownership of secure enterprise routing, switching, wireless, WAN, network services, and cloud connectivity. A deliberate balance of strategic platform improvement and responsive troubleshooting, change safety, incident response, and operational delivery. Purposeful iteration through software, APIs, Infrastructure-as-Code, Git workflows, testing, and CI/CD that reduces recurring reactive work. You might thrive in this role if you have: End-to-end ownership of secure enterprise routing, switching, wireless, WAN, network services, and cloud connectivity. A deliberate balance of strategic platform improvement and responsive troubleshooting, change safety, incident response, and operational delivery. Purposeful iteration through software, APIs, Infrastructure-as-Code, Git workflows, testing, and CI/CD that reduces recurring reactive work. Compensation, Benefits and Perks This is a position with OpenAI UK Ltd., which controls the hiring and manageme

Here’s a summary of the role: Lead a strong engineering team, deliver software that matters, and help people do the best work of their careers. This is a hands-on team management role for someone who enjoys combining people leadership, technical fluency, and modern AI-enabled ways of working to build reliable products at scale. You’ll lead engineers building secure, scalable microservices and APIs using TypeScript and AWS. You’ll partner closely with Product, Security, DevOps, and peer engineering leaders to deliver roadmap outcomes, improve team effectiveness, and create an environment where engineers can grow, own their work, and build high-quality systems with confidence. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Lead, coach, and support a team of engineers, creating clarity around priorities, ownership, expectations, and growth goals. Partner with Product, Security, DevOps, and peer engineering leaders to plan and deliver roadmap commitments while balancing quality, pace, and sustainability. Create a healthy delivery environment by improving team processes, removing blockers, supporting planning and estimation, and reinforcing strong engineering practices. Maintain enough technical depth to guide design discussions, challenge risks, review trade-offs, and support the team in building secure and maintainable systems. Use AI tools and encourage responsible AI-assisted ways of working that improve productivity while protecting privacy, security, quality, and good judgment. Support hiring, feedback, performance conversations, and career development so the team continues to grow in capability and confidence. These are the essentials you’ll need to get an interview: 8 or more years of software engineering experience, including experience leading projects and supporting or managing engineers in an agile product environment. Experience managing teams that build cloud-native microservices in AWS. Strong people leadership skills, with

Here’s a summary of the role: Build cloud software that matters, grow your technical depth, and use modern AI tooling to do your best work. This is a hands-on engineering role for someone who enjoys solving product problems, writing clean code, and helping services run reliably at scale. You’ll work on secure, scalable microservices and APIs using TypeScript, AWS , and modern engineering practices. You’ll be part of a collaborative product engineering team where you can own features, contribute to design discussions, support production systems, and keep growing across backend, cloud, and AI-assisted development workflows. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Design, build, test, and improve backend services and APIs using Node.js, TypeScript, and AWS . Take ownership of well-defined features from planning through release, including code quality, deployment, and production support . Work closely with product managers, designers, and other engineers to turn requirements into practical, reliable solutions. Contribute to technical design conversations, code reviews, and engineering standards that keep the team moving well. Use AI tools to speed up research, coding, debugging, testing, and documentation, while checking outputs carefully and applying sound judgment. Help keep systems secure, observable, and maintainable by improving monitoring, reliability, and day-to-day development practices. These are the essentials you’ll need to get an interview: 3 to 5 years of professional software engineering experience building production applications in an agile environment. Strong backend development skills with Node.js and TypeScript, including experience building APIs or microservices. Experience with React or Angular in a product engineering environment. Hands-on experience with

Here’s a summary of the role: Build software that matters, take real technical ownership, and use modern AI tooling to do your best work. This is a hands-on senior engineering role for someone who enjoys solving complex product problems, shaping robust solutions, and helping teams deliver reliable services at scale. You’ll work on secure, scalable microservices and APIs using TypeScript, AWS, and modern engineering practices. You’ll play a leading role within a collaborative product engineering team, owning complex features end to end, contributing to design and architectural decisions, supporting production systems, and helping raise the bar across backend, cloud, and AI-assisted development workflows. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Own and deliver complex backend services and APIs using Node.js, TypeScript, and AWS , from technical design through release and production support. Contribute to design and architecture discussions, making pragmatic decisions that balance delivery speed, maintainability, scalability, and security. Mentor and support less experienced engineers through code reviews, pairing, technical guidance, and day-to-day collaboration. Work closely with product managers, designers, and engineers across the team to turn requirements into practical, reliable solutions. Use AI tools to accelerate coding, debugging, testing, research, and documentation, while validating outputs carefully and applying sound judgment. Strengthen service reliability, observability, and engineering quality by improving monitoring, incident response, testing, and development practices. These are the essentials you’ll need to get an interview: 5 to 8 years of professional software engineering experience delivering production systems in an agile environment. Strong backend development s

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Are you passionate about ensuring the highest quality for cutting-edge generative AI applications? As a software quality engineer at WRITER, you'll play a critical role in shaping the reliability, performance, and trustworthiness of our AI-powered work orchestration platform. You’ll be at the forefront of defining and implementing rigorous quality strategies for our enterprise-grade LLMs and AI agents, directly impacting how hundreds of global companies unlock transformational value through AI. This is a unique chance to dive deep into the unique challenges of AI quality assurance and make a tangible difference in a rapidly evolving field. This is a hybrid role based out of our London, San Francisco, Seattle, and New York City hubs. You will report directly to the director of engineering. 🦸🏻‍♀️ What you'll do Define and implement comprehensive quality assurance strategies and test plans for our AI agents and LLM-powered applications, ensuring exceptional prod