Technical Deployment Lead

Anthropic Anthropic · AI Frontier · San Francisco, CA · Applied AI

This role leads the technical delivery of custom AI agent solutions for enterprise customers in regulated industries. The Technical Deployment Lead will own engagements end-to-end, from SOW to production deployment, working with Forward Deployed Engineers to build solutions. Responsibilities include structuring SOWs, leading technical discovery, managing engineering execution, defining product scope, owning the customer relationship, measuring value and ROI, codifying reusable assets, navigating regulatory complexity, managing scope and change, running delivery operations, and traveling to customer sites. The role requires technical depth to hold architecture conversations and executive presence for C-suite briefings, with a focus on building a new function for scaling AI agent deployments.

What you'd actually do

  1. Own the technical delivery plan for each engagement.
  2. Lead technical discovery.
  3. Run day-to-day engineering execution.
  4. Own product scoping for field engagements.
  5. Own the customer relationship throughout delivery.

Skills

Required

  • Technical delivery planning
  • SOW structuring
  • Technical discovery and workflow mapping
  • Engineering execution management
  • Product scoping and requirements documentation
  • Customer relationship management
  • Value measurement and ROI definition
  • Building reusable assets and playbooks
  • Navigating enterprise and regulatory complexity
  • Scope and change management
  • Delivery operations management
  • Executive briefings and stakeholder management
  • Experience delivering AI/ML/LLM agentic solutions
  • Experience in specialized verticals (financial services, life sciences, etc.)
  • Ability to lead architecture discussions and evaluate technical trade-offs

Nice to have

  • Experience as a founder, data scientist, engineer, researcher, or in professional services/consulting
  • Experience with RAG and vector databases
  • Experience with model serving and inference

What the JD emphasized

  • lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries
  • build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion
  • own engagements end-to-end, from SOW through production deployment
  • navigate enterprise and regulatory complexity
  • delivered AI, ML, or LLM-based agentic solutions into production
  • track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making — ideally across multiple workstreams in regulated industries
  • Thrive in ambiguity and bring structure where none exists.
  • have a builder's mindset — you're here to create a function, not join one.

Other signals

  • leading delivery of custom AI agent solutions for enterprise customers
  • building technical playbooks and defining processes for scaling
  • owning engagements end-to-end, from SOW through production deployment
  • navigating enterprise and regulatory complexity