Lead Databricks Forward Deployed Engineer - Gps

Deloitte Deloitte · Consulting

Lead Databricks Forward Deployed Engineer for Government & Public Services (GPS) clients, focusing on developing and deploying GenAI solutions. This role involves client-facing leadership, technical direction, and hands-on system design for LLM-enabled applications, RAG pipelines, and agentic workflows. Responsibilities include pod leadership, ensuring production-grade quality, and defining evaluation frameworks.

What you'd actually do

  1. Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  2. Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  3. Lead FDE pods of 2–5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  4. 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)
  5. Govern end-end RAG pipeline design—including ingestion, chunking, embedding, vector retrieval, and hybrid search—ensuring production-grade quality and scalability.

Skills

Required

  • Databricks platform technologies
  • Databricks features including Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, and Databricks Apps
  • LLM-enabled applications
  • Copilots
  • Agentic workflows
  • Assistants
  • Knowledge search experiences
  • Prompt engineering
  • Tool-use patterns
  • Human-in-the-loop controls
  • RAG pipeline design
  • Ingestion
  • Chunking
  • Embedding
  • Vector retrieval
  • Hybrid search
  • Evaluation frameworks
  • Quality
  • Hallucination risk
  • Safety
  • Latency
  • Cost
  • Governance
  • Production-quality code
  • Data pipelines powering GenAI use cases
  • Data management
  • Testing
  • CI/CD
  • Logging
  • Versioning
  • Documentation practices
  • Cloud environments (AWS, Azure, and/or Google Cloud)
  • Software engineering
  • Data engineering
  • Data science
  • Analytics engineering
  • Leading project workstreams/engagements
  • Translating business problems into AI solutions
  • Minimum Secret level security clearance

Nice to have

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

What the JD emphasized

  • Minimum Secret level security clearance
  • 6+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 6+ years of experience with Databricks including hands on experience with one of the following key platform technologies; Databricks features including Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, and Databricks Apps

Other signals

  • Lead GenAI solution development
  • 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