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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

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

Position Overview: As an Associate Service Desk Analyst, you’ll be one of the key people helping our employees get the most out of their technology. You’ll provide friendly, reliable technical support, troubleshoot hardware, software, and network issues, and make sure problems are resolved as smoothly and quickly as possible. You’ll manage incidents from start to finish, keeping users informed along the way and making sure more complex issues are escalated to the right teams when needed. You’ll also have the opportunity to contribute to improving our IT processes, documentation, and knowledge resources, helping us continuously improve the support we provide. We’re looking for someone who enjoys solving problems, helping people, and learning new things. Strong analytical, communication, and customer service skills are important, as well as a proactive attitude and the motivation to grow your career within the organization. You’ll work both independently and as part of a global team, so being comfortable collaborating with people across different locations and teams is key. Key Responsibilities Deliver comprehensive onsite and remote technical support, ensuring rapid resolution of hardware, software, and network issues to maintain optimal business continuity and user productivity. Proactively manage and update service tickets throughout the incident lifecycle, leveraging advanced troubleshooting skills and maintaining clear, professional communication with stakeholders at every stage. Demonstrate in-depth proficiency with Diligent’s core technologies—including Windows, Mac OS, and O365— applying best practices to resolve complex technical challenges and enhance the end-user experience. Serve as a subject matter resource for both hardware and software support, collaborating with crossfunctional teams to drive continuous improvement in IT service delivery. Actively contribute to the development and maintenance of knowledge base resources, synthesizing insights fr

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: As an ideal candidate you have a good understanding of how highly scalable and reliable production infrastructure is built. Most of our backend infrastructure is written in Rust. So familiarity with a compiled language such as C++, Rust, or Go is highly beneficial. RESPONSIBILITIES: Build the SpaceXAI API that serves our models to developers worldwide Own the end-to-end system responsible for high-throughput inference, handling billions of tokens per minute with low latency and high availability, including model serving infrastructure, request routing, SDK development, rate limiting, observability, and efficient scaling BASIC QUALIFICATIONS: Expert knowledge of either Rust or C++ Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems Knowledge of service observability and reliability best practices Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB PREFERRED SKILLS AND EXPERIENCE: Experience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM) Experience designing or building with agent SDKs and agent orchestration frameworks Experience with Docker, Kubernetes, and containerized applicatio

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in London. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and deplo

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! At Figma we believe design doesn’t end in a file or with your designer - it includes everything that goes into the product you ship: the production code that ties it all together, the systems and developer tools that make that code reliable, the context you provide to our AI agents, and the documentation that keeps everyone on the same page. The Roundtripping Area at Figma is redefining how Designers, PMs and Engineers collaborate. We are responsible for agentic workflows enabling ideation and prototyping on production codebases as well as accelerating the journey from design to code. In 2023, we launched Dev Mode, a suite of features that give developers everything they need to navigate design files and transform designs into code. In 2025, we introduced Figma’s MCP, accelerating how ideas get to production. Looking to the future, we aim to further reduce the barriers between design to code and code to design allowing ideation, prototyping and productionalising to happen seamlessly where it most makes sense. Our Roundtripping team is expanding, and we’re hiring AI Product Engineers across multiple levels in the UK. We’re looking for people who have built generative AI products and are eager to lead AI efforts end-to-end, from early ideas to production. Join us in shaping the future of AI at Figma. What you’ll do at Figma: Build and evolve Dev Mode our MCP tools and Make, Figma’s leading tools for dev/design collaboration Take part in building new 0→1 products within the agentic coding space Col

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbatical

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 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

Overview: We are looking for a Product Manager to support the build, rollout, adoption, and continuous improvement of AI-powered products used across Guidepoint’s expert-network operations. This role sits at the intersection of product management, product operations, workflow automation, AI adoption, and internal tools. The ideal candidate is a hands-on problem solver who can work closely with users, engineering, QA, design, operations, and leadership to turn high-friction workflows into reliable, scalable product systems. The Product Manager will support a portfolio of mature and emerging initiatives by writing clear requirements, managing user feedback, looking at adoption, usage data & analytics, triaging issues, supporting UAT and helping teams make data-driven product improvements. This role is especially important as Guidepoint expands its use of AI, automation, and human-in-the-loop workflows across complex operational processes. What You’ll Do: Product Delivery & Execution Partner with engineering, QA, UX, and business stakeholders to support timely and high-quality delivery of product improvements. Participate in sprint planning, backlog refinement, UAT, release readiness, and post-release review. Help ensure features are tested against real user workflows, edge cases, business rules, and operational expectations. Support rollout planning, user onboarding, training, and adoption follow-ups for new and existing product capabilities. Product Operations & Workflow Support Act as a day-to-day product contact for users Triage bug reports, user questions, change requests, and product feedback. Translate recurring themes into clear product requirements, tickets, acceptance criteria, and follow-up actions. Maintain strong product hygiene across Jira, Confluence, release notes, user documentation, and training materials. AI Workflows & Tools Work with product and engineering teams to ensure AI-driven features are usable, measurable, and aligned with

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 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

About the Role: The Program Manager executes Technology Capital Builds by creating tight alignment across Real Estate and Workplace Services, Corporate IT, Corporate Security and other partner teams to design and deliver technical solutions for capital build outs, including new office buildout and remodels, industrial labs, datacenters and secured facilities. This includes all low voltage, ISP connectivity, network infrastructure, audio visual, physical security and related IT scopes of work. In this role, you will: Ensure new sites launch with secure and reliable ISP connectivity, network infrastructure, and low voltage systems that are ready to support employees from day one. Deliver Capital Builds commitments through effective coordination across internal teams, construction partners, and vendors, achieving outcomes on scope, schedule, budget, and quality. Ensure AV systems across conference rooms, training spaces, all hands venues, digital signage, and wayfinding deliver a consistent and dependable user experience. Ensure access control, surveillance, and intrusion detection systems are integrated into the built environment and aligned with enterprise security requirements. Provide leadership with clear visibility into portfolio status, key decisions, dependencies, and emerging risks. Establish standards, drawing packages, specifications, and documentation that enable repeatable execution and operational consistency across the global portfolio. Ensure disciplined stewardship of procurement, budgets, and vendor investments across the Capital Builds portfolio. Identify and mitigate delivery risks early to protect project outcomes, business continuity, and operational readiness. Ensure all systems are commissioned, documented, and transitioned to support teams with clear ownership and support models in place. You might thrive in this role if you have: Strong project and program management capabilities. Strong knowledge of the architectural design process (schematic

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 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 At WRITER, our mission to expand human capacity with superintelligence relies on a foundational truth: our platform must be available, performant, and reliable, 24/7. As an Infrastructure engineer, you'll be at the heart of making this a reality, impacting every enterprise customer who trusts us with their AI-powered workflows. This isn't just about keeping the lights on; it's about pushing the boundaries of what's possible, proactively identifying and solving complex systemic challenges, and laying the groundwork for our rapid growth and the evolving demands of enterprise generative AI. You'll build resilient systems, automate across the stack, and champion reliability best practices, directly enabling our ambitious product roadmap and ensuring our customers always have access to the powerful tools they need. This is a hybrid position, based out of our New York City or London hubs. You'll report to our director of engineering. 🦸🏻‍♀️ What you'll do Technical