Infrastructure Security Engineer in London

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

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Threat Intelligence Analyst Overview This is an exciting position for a Lead Threat Intelligence Analyst to join Vocalink’s dedicated Threat Intelligence function. You will be play an integral leading role in the Vocalink Threat Intelligence Team, working closely with the SOC and internal security teams to deliver actionable intelligence. You will support a diverse range of customers and contribute to key initiatives such as threat hunting, vulnerability management, and insider threat detection. Collaboration is at the heart of this position. You will work alongside Mastercard’s global threat intelligence capabilities and engage proactively with a wide network of stakeholders, including vendors, industry groups, our customers, and government organisations. This is a unique chance to help shape and grow a fast-evolving threat intelligence capability that serves Vocalink and its customers. If you are passionate about cyber security and eager to make an impact, this role offers an exciting platform to develop your leadership expertise and to help to grow and mature a threat intelligence function in a critical national infrastructure provider. Role Lead the day-to-day operations of the threat intelligence function within the Vocalink Security Operations Cent

🚀 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

🚀 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

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 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

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 -

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Solutions Architecture team works with our largest, most complex users to understand their technical requirements and map those to Stripe technology. As a Solutions Architect, you'll partner with Sales to technically qualify new business opportunities, demonstrate the art of the possible with the Stripe Platform, and design robust technical solutions to enable payment transactions, manage money movements and simplify financial operational processes. What you’ll do You are an experienced technologist with a blend of technical depth and strong business consulting skills. You can write code, but prefer to spend your time working with users to create Stripe solutions to support customer business objectives in complex, mission-critical environments. You'll think strategically about the art of the possible for the user’s business, and be able to clearly articulate that in a way that informs and builds confidence in Stripe’s technology. You should be able to engage and motivate cross-functionally both internally and within our customer’s organisations at all levels, from Cx to Product Engineering. You'll have a track record of delivering exceptional customer results as part of a pre-sales team, but a history of deep technical work that gives you the ability to be credible with any audience. Responsibilities Engage with Chief Technical Officers, engineering leads, and other technical leads at key users to share technology roadmaps, demonstra

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

About Yondr Yondr is a disruptor. We challenge convention and simplify complexity. A global developer, owner operator and service provider of data centers, we deliver complex data center capacity needs for the world’s largest tech companies. Our exponential growth sees us looking for extraordinary people to help accelerate us towards our vision: a tomorrow without constraints. But we can’t do this without you. About the Role Yondr Group, a global developer, owner and operator of hyperscale data centres, is seeking an experienced lawyer to support its growing EMEA business. Reporting to the Legal Director EMEA, the successful candidate will act as the primary legal adviser to Yondr's design, construction and operations teams across the EMEA region. The role will support the full project lifecycle, from development, procurement and financing through construction, completion and operations. The successful candidate will work closely with project delivery, commercial, procurement and operational teams, supporting projects involving a range of delivery models, funding structures and stakeholders, including customers, lenders, investors, contractors, consultants, utility providers and suppliers. The role will be expected to operate independently on day-to-day matters, leading legal support across Yondr's EMEA construction and operations portfolio whilst managing legal risk and stakeholder requirements. This includes ensuring project documentation appropriately reflects contractual, leasing, funding and other stakeholder requirements. Minimum Qualifications Qualified solicitor with 6+ years' PQE with significant experience in primarily non-contentious construction, infrastructure, energy or data centre projects (preferred). Have trained at a reputable law firm or within the legal function of a reputable data centre, construction, infrastructure, energy or technology business. Experience negotiating and managing com

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

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 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

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 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