Staff Software Engineer, Foundation Model Inference

P-1930

At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI.

We're hiring across multiple teams in our AI Engineering org, including the FMAPI (Foundation Model APIs) team — the unified serving layer for large language models across real-time and batch inference, powering model inference at enterprise scale. We are looking to hire high-agency engineers who bridge the gap between technical execution and product strategy.

The impact you will have:

• Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama)
• Shape the direction of the FMAPI product — from roadmap to execution — by leveraging deep customer empathy and direct engagement with enterprise users and model providers
• Improve reliability, latency, and efficiency of distributed AI workloads
• Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences
• Shape how developers and data scientists build and interact with AI on Databricks

What we look for:

• 8+ years of experience in backend or infrastructure engineering
• Experience with distributed systems, scalable APIs, or cloud-native infrastructure
• Strong product and ownership mindset, with a focus on shipping user-facing value
• Experience with real-time serving, ML infrastructure, or GPU orchestration
• Familiarity with service-oriented architecture, deployment pipelines, and system observability
• Strong programming skills in Scala, Go, or Python

Bonus points for:

• Exposure to platforms like SageMaker, Vertex AI, or Azure ML
• Built products that support AI workflows