Automation Operation System Engineer in United Kingdom

About the job Help shape the first moments of life for the next generation of AI processors. You'll lead the bring-up and characterisation of Graphcore's silicon devices and system platforms. Your work will ensure products perform reliably before they reach customers. You'll build and lead a team that develops characterisation plans, automates testing, and analyses results across silicon and system platforms. You'll work closely with architecture, silicon, hardware, operations and product teams to solve complex technical challenges. This is a hands-on technical leadership role with the opportunity to influence product design, shape new capabilities, and build a team from the ground up. The team and culture You'll join a newly formed team within Manufacturing Operations and help define how bring-up and characterisation is delivered at Graphcore. Your decisions will shape the team's direction as it grows. The team works closely with colleagues across Bristol, Cambridge and Taiwan. Success comes from solving problems together, sharing data, and making informed engineering decisions. You'll be trusted to take ownership, remove blockers, and improve how work is done. We value people who speak up, challenge assumptions, and turn ideas into practical solutions. What we're looking for Essential Proven track record of delivering technical outcomes as an individual contributor, manager, or project manager, with strong communication and stakeholder management skills. Solid experie

About the job Build the cloud platform that puts Graphcore AI systems into real use. As a Senior Cloud Engineer, you will develop and operate private cloud services for Graphcore teams and users. You will turn product and user requirements into reliable, deployed services. Your work will support large-scale AI systems built from Graphcore hardware, high-performance servers, networks and storage. These systems help engineers validate, benchmark and optimise the platforms behind advanced AI compute. You will use Infrastructure-as-Code, observability and automation to deploy, test and improve cloud infrastructure. You will also work with datacentre, software and product teams to keep critical systems performing. This is hands-on engineering with real ownership. You will often work with pre-release hardware and software, where judgement and pace matter. The team and culture The Cloud Platform Team builds the systems that give internal users and customers access to Graphcore AI infrastructure. Work moves from requirements to deployed services, with engineers close to the users and systems they support. You will work across Software Platform, Datacentre Operations and Product Development. Decisions are shaped by technical evidence, user needs and the realities of operating critical infrastructure. This team suits engineers who take responsibility, speak up and move quickly. You will be trusted to work independently, solve hard platform problems and keep services available. &

About the job Build the cloud platform that powers Graphcore’s next generation AI systems. As a Principal Cloud Engineer, you will help develop, deploy and operate cloud services across Graphcore’s AI infrastructure. You will work on private and public cloud systems used by internal teams and customers. Your work will shape how high-performance AI systems are integrated, validated, benchmarked and optimised. You will help keep complex infrastructure reliable, observable and ready for demanding workloads. You will own significant technical initiatives, from OpenStack-based services to Infrastructure-as-Code automation. You will also mentor engineers and turn user needs into services that perform at scale. This role puts you close to pre-release hardware, advanced systems and real product challenges. The Team and Culture The Cloud Platform Team sits within Software Platform and works closely with Software Platform, Datacentre Operations and Product Development. The team builds systems for internal users and customers, often using new components before they are proven. Work moves through practical engineering, clear ownership and fast feedback from users. You will be expected to take responsibility, speak up early and lead critical infrastructure work without close oversight. Decisions are grounded in evidence from benchmarks, observability data and operational performance. The team values engineers who can think big, act fast and bring others with them. What we’re

About the job Lead the team that proves our AI silicon performs reliably before it reaches customers. You will build and lead Graphcore's characterisation capability for next generation silicon and system platforms. Your work will help ensure our products perform consistently across real world conditions. You will define bring up and characterisation strategies, lead technical execution, and shape the lab infrastructure needed for success. You'll work across silicon, hardware, manufacturing, architecture and product teams to solve complex engineering challenges. This is a hands on leadership role with the opportunity to influence both product design and how Graphcore validates future AI systems. The team and culture This is a newly formed team within Manufacturing Operations. You'll have the opportunity to establish how the team works while building strong partnerships across engineering and operations. Day to day, you'll work closely with architecture, silicon, hardware, production test and product teams. Decisions are driven by data, technical evidence and close collaboration across disciplines. We value ownership and clear communication. You'll be trusted to lead technical direction, remove blockers and help teams make progress with confidence. What we're looking for Essential Proven track record of delivering complex technical projects as an individual contributor, manager, or project manager, with the ability to work independently and drive execution. Strong expert

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 ownersh

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 & Wo

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, au

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 Substrate is the team responsible for Palantir’s core production infrastructure — 100s of K8s clusters — from on-prem to the major cloud hyperscalers, whether they are internet-connected or air-gapped, small hardware footprint or large. As a Senior Software Engineer on Substrate, you will design and build Palantir’s managed Kubernetes product offerings across all these environments. You and your team will be responsible for bootstrapping and operating the entire fleet of K8s clusters with zero manual steps by building industry leading tooling and contributing to core CNCF components. You will also be responsible for ensuring scale, stability and security across a matrix of compliance regimes and hosting infrastructure types. Your team culture emphasizes engineering rigor and operational excellence at scale. This means issues in production should be pre-empted and deeply root-caused, and investments in automation and self-healing systems are key. If you’re excited about infrastructure at scale and working with Kubernetes, this is the right role for you. Core Responsibilities Deliver a container runtime to challenging new environment types - new clouds, on pre

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role As a Manager of Forward Deployed Engineering on Notion’s Services team, you will lead a team responsible for the hands-on technical delivery of our most complex customer engagements. Your team will design, build, and deploy production-ready solutions that help enterprise customers integrate Notion as the operating layer for their business. You will combine people leadership, technical judgment, and customer-facing delivery. You will coach Forward Deployed Engineers through discovery, architecture, implementation, and launch while remaining close enough to the work to guide difficult technical decisions, unblock delivery, and bui

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (covera

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 abstrac

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and ac

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and ac

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environme

About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform is comprised of three products: THG Commerce, THG Studios, THG Fulfilment. Each represents a single, unified solution, overcoming challenges and taking brands direct-to-consumer. Our client portfolio includes globally recognised brands such as Coca-Cola, Nestle, Elemis, Homebase, and Proctor & Gamble. The Role We are seeking a talented and commercially astute Data Scientist to join our dynamic team tackling Fraud, Payments and Finance. In this multi-focus role, you will be responsible for protecting our global e-commerce operations from fraud, optimising our payments performance and driving profitability and automation initiatives within Finance. Working with vast, complex datasets, the work will involve combatting online fraud using our award-winning THG Detect platform and driving payments optimisation by increasing authorisation rates, while also using the latest AI software and Google Cloud Platform (GCP) infrastructure to build complex data solutions and applications. This role requires a blend of strong technical skills, commercial acumen, and effective communication to translate complex data insights into tangible business value. Responsibilities: Optimise Fraud Detection: Continuously improve automated decision-making in our in-house THG Detect platform using machine learning and decision rules