Databricks
AI Engineer - FDE (Forward Deployed Engineer)
About this role
Databricks seeks an experienced AI Engineer to join its Forward Deployed Engineering team, delivering professional services to help enterprise customers build and productionize GenAI and LLM applications at scale. This role combines technical expertise in production AI systems with customer-facing advisory work, influencing product strategy and thought leadership across the industry.
What you'll do
- Develop and deploy production-grade GenAI solutions using techniques like RAG, multi-agent systems, and fine-tuning to solve customer problems
- Own end-to-end rollouts of consumer and internally facing GenAI applications, including evaluation and optimization
- Serve as a trusted technical advisor to enterprise customers across various industries and use cases
- Collaborate cross-functionally with product and engineering teams to shape roadmap priorities and influence strategic initiatives
- Present at industry conferences and establish thought leadership internally and externally
- Travel to customer sites approximately once every 4-8 weeks as needed
What they're looking for
- GenAI application development (RAG, multi-agent systems, Text2SQL, fine-tuning)
- LLM frameworks and tools (HuggingFace, LangChain, DSPy)
- Production ML deployment on AWS, Azure, or GCP
- Data science and ML tools (pandas, scikit-learn, PyTorch)
- Apache Spark and distributed data processing
- Technical communication and teaching to diverse audiences
- Databricks Intelligence Platform
- ML evaluation and optimization techniques
Opens the official application on the employer’s site. No login required.
Databricks
Databricks builds a unified data and AI platform that combines database systems, distributed computing, and generative AI capabilities across multi-cloud infrastructure. The company is hiring software engineers, applied AI engineers, and web engineers to develop core database engines, ML/AI features, inference systems, and user-facing products.
- Website
- databricks.com
Likely interview questions
- Describe a GenAI application you've deployed to production—what were the key technical challenges and how did you evaluate its performance?
- How have you optimized LLM applications for cost, latency, or accuracy in a production environment?