Top Tech Jobs & Startup Jobs in London

Manages Anthropic’s Technical Deployment team for Financial Services, overseeing enterprise AI engagement portfolios from scoping through production deployment. Responsibilities include hiring and developing Technical Deployment Leads, ensuring delivery quality, managing executive customer relationships, staffing engagements, leading complex deployments, establishing technical playbooks and evaluation frameworks, partnering with Sales and Marketing, and translating field insights into product and research strategy. The role requires 25–50% travel to customer sites.

Serve as a pre-sales technical architect for Anthropic’s global and regional system integrator and cloud partners. Develop industry-specific generative AI solutions, reference architectures, and deployment best practices; support strategic customer deals; troubleshoot complex technical issues; enable partner engineering teams; lead technical workshops, hackathons, and events; and relay partner feedback to inform product and go-to-market strategies.

Serve as a technical advisor to high-growth companies building products with Claude. Partner with engineering teams through pair programming, architecture reviews, code contributions, prototypes, evaluation frameworks, documentation, and scalable AI application design. Create developer resources, identify cross-engagement patterns, support hackathons and workshops, and collaborate with Anthropic’s product and engineering teams. The role requires production LLM application experience, strong Python skills, customer-facing communication, and travel to customer sites.

Partner with startup founders and engineering teams to architect, evaluate, deploy, and scale LLM applications on the Claude Developer Platform. Serve as a technical advisor throughout adoption, lead technical evaluations, develop AI performance frameworks, communicate customer insights to Product and Engineering, and represent Anthropic at customer sites and industry events.

Build and deploy production AI applications using Claude models within enterprise customer environments. Develop MCP servers, sub-agents, and agent skills; provide deployment support; identify repeatable implementation patterns; and collaborate with Product and Engineering. The role requires customer discovery, technical solution development, strong communication, autonomous execution, and frequent travel to customer sites.

Lead the sales team for EMEA at Anthropic, focusing on partnerships with nonprofits and educational institutions. Drive revenue while building and managing a high-performing team. Navigate complex sales cycles and stakeholder ecosystems to achieve strategic goals.

Build and operate large-scale observability infrastructure, including telemetry pipelines, instrumentation libraries, eBPF tracing, continuous profiling, cross-signal correlation, unified query tools, and AI-assisted diagnostics. Improve reliability, efficiency, detection, and incident resolution across massive GPU, TPU, and Trainium infrastructure while partnering with research, inference, product, and infrastructure teams.

Build internal full-stack products across backend, frontend, and infrastructure. Work directly with users to identify needs, create reusable platforms and abstractions, make product and prioritization decisions, and independently ship solutions. Continuously iterate based on feedback while empowering less-technical users. The role requires strong systems thinking, comfort with ambiguity, and proficiency in Python, TypeScript, and React.

Leads European data center capacity transactions from RFP and developer sourcing through term-sheet negotiation, LOI, due diligence, and lease execution. Coordinates legal, finance, engineering, network, government relations, and deployment stakeholders; manages timelines, risks, regulatory requirements, and construction-ready infrastructure development. Builds scalable transaction processes and playbooks while partnering on European market, site, and counterparty strategy.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.