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Lead Forward Deployed Engineer, Microsoft AI & Data

Job in Gilbert, Maricopa County, Arizona, 85233, USA
Listing for: PowerToFly
Full Time position
Listed on 2026-05-31
Job specializations:
  • Software Development
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

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.

Work you'll do

As a Lead Microsoft AI&Data 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 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 engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required

qualifications
  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering.
  • 1+ years of hands‑on experience building and deploying GenAI/LLM‑powered solutions in client or production…
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