AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector - Databricks - Virginia

Databricks is a data and AI company that helps organizations build and productionize AI applications. The AI Forward Deployed Engineering team is seeking an AI Engineer to develop cutting-edge GenAI solutions and serve as a trusted technical advisor to federal government customers.

Responsibilities
• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

Skills
• U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information
• Experience working with U.S. federal civilian, state, or local agencies
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.)
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed