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. As a Lead Databricks FDE, you will work closely with strategic clients to develop and deploy GenAI solutions.

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.
• 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, including 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.
• 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.
• Guide architecture of data pipelines powering GenAI use cases.
• Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices.

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.
• Ability to work independently and collaborate as part of a team.
• Meticulous attention to detail and quality of work product.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• 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.

Qualifications

• Required: 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. Ability to work independently and collaborate as part of a team. Meticulous attention to detail and quality of work product. Strong interpersonal skills and professional demeanor. Ability to meet deadlines. 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.
• Preferred: Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking).