Databricks
AI Engineer – Forward Deployed Engineering (AI FDE), U.S. Public Sector (Federal Focus)
$182K–$250K
Maryland +3 · Remote · Full-time · Posted Aug 28, 2026
- Location
- Maryland
Virginia
Washington, D.C.
Remote - Washington D.C. - Experience
- Extensive years of hands-on industry data science experience; no specific number of years stated.
- Education
- Graduate degree in a quantitative discipline (such as Computer Science, Engineering, Statistics, or Operations Research) or equivalent practical experience.
- Visa sponsorship
- U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information.
About the job
Build and productionize customer-facing generative AI solutions for public-sector clients, advise customers, and collaborate with Databricks teams on product direction.
What you'll do
- Develop GenAI solutions and own production rollouts of applications.
- Advise customers and communicate technical concepts to varied audiences.
- Collaborate with product and engineering teams to shape priorities and the product roadmap.
What they ask for
- Experience building GenAI applications, including approaches such as RAG, multi-agent systems, Text2SQL, or fine-tuning.
- Expertise deploying production-grade GenAI applications, including evaluation and optimization.
- Hands-on industry data science experience and experience building production-grade ML deployments on AWS, Azure, or GCP.
- Graduate degree in a quantitative discipline or equivalent practical experience.
Nice to have
- Experience with the Databricks Intelligence Platform and Apache Spark to process large-scale distributed datasets.
- Active Secret or higher clearance is strongly encouraged.
Pay
$182,000 — $250,208 USD (salary range; non-commissionable role or on-target earnings for commissionable roles)
Tools
HuggingFace, LangChain, DSPy, pandas, scikit-learn, PyTorch, AWS, Azure
AI focus
Develop and productionize GenAI applications using techniques including RAG, multi-agent systems, Text2SQL, and fine-tuning; perform evaluation and optimization.
Model-written summary · the original posting is authoritative