Top Tech Jobs & Startup Jobs in London

Lead end-to-end deployment of frontier AI models for strategic customers, from discovery and system design through production rollout. Build full-stack systems, contribute production code, guide customer adoption, manage delivery trade-offs, and codify reusable tools and playbooks. Partner with customer engineering, Product, Research, Security, GRC, Partnerships, and GTM teams while providing feedback to improve models and product roadmaps. Professional fluency in Spanish and English is required, with travel up to 50%.

Build backend infrastructure and customer-facing workflows for AI agents in secure enterprise cloud environments. Develop Go services and APIs, cloud provisioning, orchestration for long-running parallel tasks, integrations with developer tools, and security controls such as permissions, credential handling, isolation, and auditability. Own production quality through testing, rollouts, observability, performance, and reliability while collaborating with customers, frontend, infrastructure, and security teams.

Lead post-sales enablement for OpenAI products, including ChatGPT Enterprise and Agents. Design and deliver onboarding, workshops, advanced training, executive briefings, and adoption programs for business and technical audiences. Drive activation, sustained usage, product expansion, and measurable business value across enterprise customers. Develop reusable training assets and playbooks, gather customer feedback, identify adoption patterns, and collaborate with Sales, Solution Architects, Delivery Leads, and product teams.

Own the technical strategy and customer journey for a portfolio of education institutions adopting OpenAI solutions. Lead discovery, architecture design, technical evaluations, prototypes, adoption roadmaps, governance, deployment readiness, and value realization. Build relationships with executive, academic, research, and technical stakeholders while coordinating specialist teams. Translate education needs into responsible AI use cases and reusable architectures, track adoption and customer impact, and provide feedback to Product, Engineering, and Research.

As a Software Engineer in Infrastructure Reliability, you'll design and build resilient systems, optimize performance, improve automation, and collaborate with teams to enhance infrastructure reliability.

Develop and scale new LLM architectures, run and analyze training experiments, debug and optimize model and compute performance, and contribute to training and inference infrastructure. Work collaboratively to improve model intelligence, efficiency, and capabilities. Role is hybrid, based in London with relocation assistance.

Design, build, evaluate, and deploy AI systems for enterprise customers. Responsibilities include creating prototypes and production integrations, diagnosing implementation issues, making decisions about reliability, security, governance, latency, cost, and safety, and helping customers scale adoption. The role also develops reusable architectures, tooling, playbooks, and technical guidance while partnering with customer and internal engineering, product, research, security, and go-to-market teams.

Build and operate backend systems, workflow tooling, and data pipelines to support lawful data access requests. Implement least-privilege, audit trails, approval gates, and data-minimization. Partner with Legal and Operations, automate responsibly, and own production reliability, observability, incident response, and documentation while shaping privacy infrastructure.

Build and operate backend systems, workflow tooling, and data pipelines for lawful data access requests. Implement least-privilege access, audit trails, data minimization, and approval gates. Partner with Legal and Operations to translate requirements into secure, auditable, and operator-friendly systems. Own production reliability, testing, observability, and incident response while defining reusable privacy infrastructure.

Design and build distributed systems for large-scale AI training, focusing on performance, stability, monitoring, and debugging of infrastructure.