Lead Databricks Forward Deployed Engineer - GPS

About the role

The Deloitte AI & Engineering team transforms technology platforms, drives innovation, and makes a significant impact on clients' success. You'll work alongside talented professionals reimagining and reengineering operations and processes critical to businesses.

Responsibilities

• Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders.
• 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.
• 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.
• Cross-coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
• Mentor and develop junior FDEs.
• Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms.
• Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
• Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.
• Guide architecture of data pipelines powering GenAI use cases.
• Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices.
• Deeply familiar with cloud environments (AWS, Azure, and/or Google Cloud).

Requirements

• Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
• Minimum Secret level security clearance.
• 10+ years of experience in software engineering, data engineering, data science, or analytics engineering.
• 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.
• 6+ years of experience leading project workstreams/engagements and translating business problems into AI solutions.
• 5+ years of experience building reliable, maintainable, and well-documented code and CI/CD DevOps in Databricks.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

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 evaluation.
• Experience 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.
• Familiarity with security, privacy, and compliance considerations.