Lead Forward Deployed Engineer - Databricks (Charlotte)

Position Summary






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 leadersLead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scalingNavigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared visionRepresent 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 healthEnforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gatesCoordinate 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 controlsGovern 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 codeGuide architecture of data pipelines powering GenAI use casesEnforce strong data management, testing, CI/CD, logging, versioning, and documentation practicesDeep 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 Engineering7+ years of experience in software engineering, data engineering, data science, or analytics engineering1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions1+ years of experience building reliable, maintainable, and well-documented code Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serveLimited immigration sponsorship may be available
Preferred qualifications
Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluationExperience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures Experience operating within hybrid onshore/offshore teams Familiarity with security, privacy, and compliance considerations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $189,200 to $372,900.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at View email address on apply.placed-app.com.






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Requisition code: 350642


Job ID


350642
Engineering and Product
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