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Technical Deployment Lead, Applied AI

Job in London, Greater London, W1B, England, UK
Listing for: Anthropic
Full Time position
Listed on 2026-03-04
Job specializations:
  • IT/Tech
    Systems Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes.

This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world class delivery, and bring insights back to our product and research teams on a regular basis.

You'll own engagements end-to-end, from SOW through production deployment. You'll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organizational complexity that comes with deploying AI agents in enterprise environments. You need to be technical enough to hold architecture conversations with engineering stakeholders and polished enough to run executive briefings with C‑suite sponsors.

Responsibilities
  • Own the technical delivery plan for each engagement. Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses – translate customer business objectives into a sequenced roadmap that FDEs execute against.
  • Lead technical discovery: map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.
  • Run day‑to‑day engineering execution and delivery across Anthropic and customer teams. Keep progress unblocked and sequenced. Make real‑time trade‑offs on scope and priority to protect the critical path.
  • Own product scoping for field engagements: define the MVP, author requirements documentation, prioritize the engineering backlog, and manage scope against success criteria as requirements evolve.
  • Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic’s technical credibility with senior business and engineering leaders.
  • Own value measurement and ROI: define impact hypotheses, set baselines and KPIs, run pre‑ and post‑deployment measurement, and report outcomes to executive sponsors.
  • Codify reusable solution patterns, evaluation frameworks, and technical playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.
  • Navigate enterprise and regulatory complexity: security reviews, legal approvals, procurement processes, compliance requirements, and organizational dynamics.
  • Manage scope and change: handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and elevate with clear context when needed.
  • Run delivery operations: sprint ceremonies, milestone reviews, and progress reporting.
  • Travel to customer sites to build relationships, unblock delivery, and accelerate adoption (25–50% expected).
You May Be a Good Fit If You
  • Have 5+ years of customer‑facing technical delivery leadership — this could be technical engagement management, technical program management, or technical product management, founders/startups, technical‑adjacent backgrounds, professional services, consulting, or enterprise software.
  • Have delivered AI, ML, or LLM‑based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
  • Can lead architecture discussions with engineering stakeholders, evaluate technical trade‑offs, and pressure‑test technical decisions. You won’t write production code, but you will own the technical direction of engagements alongside FDEs.
  • Have a track…
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