Lead Anthropic Forward Deployed Engineer - Gps

Lead engineer responsible for deploying GenAI solutions, architecting LLM applications, governing RAG pipelines, and defining evaluation frameworks for enterprise clients. Focuses on production-grade quality, scalability, and client-facing technical leadership.

What you'd actually do

  1. Serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte’s most strategic clients.
  2. Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  3. Govern end-to-end RAG pipeline design—including ingestion, chunking, embedding, vector retrieval, and hybrid search—ensuring production-grade quality and scalability.
  4. Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.
  5. Lead FDE pods of 2–5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health

Skills

Required

  • Software engineering
  • Data engineering
  • Data science
  • Analytics engineering
  • Building and deploying GenAI/LLM-powered solutions
  • Anthropic platform technologies (Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code)
  • Leading project workstreams/engagements
  • Translating business problems into AI solutions
  • Building reliable, maintainable, and well-documented code
  • Cloud environments (AWS, Azure, and/or Google Cloud)

Nice to have

  • Prompt engineering
  • Tool-use patterns
  • Human-in-the-loop controls
  • RAG pipeline design
  • Ingestion, chunking, embedding, vector retrieval, and hybrid search
  • Evaluation frameworks (quality, hallucination risk, safety, latency, cost, governance)
  • Data management
  • Testing
  • CI/CD
  • Logging
  • Versioning
  • Documentation practices

What the JD emphasized

  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Anthropic including hands on experience with one of the following key platform technologies; Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code

Other signals

  • Deploying GenAI solutions into production
  • Architect and oversee delivery of LLM-enabled applications
  • Govern end-to-end RAG pipeline design
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance