Lead Forward Deployed Engineer, Frontier GenAI

# Lead Forward Deployed Engineer, Frontier GenAIDeloitte

Be an Early Applicant Full Timelead Hybrid Baltimore , Maryland, USPosted Today## Resume Keywords to Include Make sure these keywords appear in your resume to improve ATS scoring

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Job Description At Deloitte, Forward Deployed Engineers (FDE) 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 10/30/2026.Work you'll doAs a Lead Frontier GenAI 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 FDEsGenAI 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 frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations
* Review and contribute to production-quality code
* Guide architecture of data pipelines powering GenAI use cases
* Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
* Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)
The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming…