Databricks GenAI Engineer - Client Impact Leader

Deloitte France; San Francisco (CA); On-site; USD 135,000 - 265,000; Full time

Job summary

Deloitte is seeking a Databricks Forward Deployed Engineer (FDE) to rapidly prototype and deliver GenAI-enabled solutions for enterprise clients in the U.S. You will work with senior client teams to translate business needs into impactful AI outcomes.

As part of an FDE pod, you will build production-quality code, apply scalable patterns, and contribute reusable assets while mentoring teammates. Travel up to 50% may be required as projects evolve.

Qualifications

• Bachelor's degree in CS, Data Science or Engineering.
• 3+ years of software, data or analytics engineering.
• 1+ year hands-on GenAI/LLM-powered solutions in client or production environments.
• 1+ year experience with Databricks (DBRX/MLflow/Vector Search).
• 1+ year leading project workstreams and translating business problems into AI solutions.
• Ability to travel 50% on average across clients and industries.

Responsibilities

• Embed with clients to identify business needs and translate GenAI use cases into solutions.
• Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
• Lead working sessions to shape solutions and drive client outcomes.
• Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
• Contribute independently within an FDE pod while mentoring newer team members.
• Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.

Skills

Software engineering

Data engineering

GenAI-powered solutions

Project leadership

Education

Bachelor's degree in CS/DS/Engineering

Tools

Databricks Platform

MLflow

Vector Search

Spark

Airflow/dbt

Job description

Deloitte is seeking a Databricks Forward Deployed Engineer (FDE) to rapidly prototype and deliver GenAI-enabled solutions for enterprise clients in the U.S. You will work with senior client teams to translate business needs into impactful AI outcomes.

As part of an FDE pod, you will build production-quality code, apply scalable patterns, and contribute reusable assets while mentoring teammates. Travel up to 50% may be required as projects evolve.