Lead Forward Deployed Engineer - Databricks

At Deloitte, Lead Forward Deployed Engineers (LFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise.

If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Lead Databricks FDE, you will 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.

You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team.

You'll translate engineering trade-offs into clear decisions for client leaders when needed.

Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart.

Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement


* Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders


* Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling


* Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision


* Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance


* Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health


* Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates


* Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.


* Mentor and develop junior FDEs

GenAI Solution Development


* 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)


* Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls


* Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.


* Define evaluation frame...