Staff Software Engineer- Foundation Model Inference

About the role

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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.

The Foundation Model Inference team is the backbone of Databricks’ generative AI capabilities. We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance. Our Foundation Model APIs provide a unified platform that gives customers access to LLMs with the governance, flexibility, and scalability required for enterprise production workloads.

We are looking for high-agency engineers who are excited to work on powering model inference at enterprise scale.

Check out our recent blog post: Reliable LLM Inference at Scale

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)

- 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

- Experience with real-time serving, ML infrastructure, or GPU orchestration

- Familiarity with service-oriented architecture, deployment pipelines, and system observability

Bonus points for:

- Exposure to platforms like SageMaker, Vertex AI, or Azure ML

- Contributions to OSS projects like MLflow, PyTorch, Ray, vLLM, SGLang

- Built developer platforms or internal tools supporting AI workflows