Staff Software Engineer, Foundation Model API
Build and shape the Foundation Model API serving layer for large-scale LLM inference (partner and self-hosted models) at Databricks. Requires 8+ years backend/infra engineering experience with distributed systems, ML infrastructure, and a strong product ownership mindset.
About the job
Impact
- 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
Requirements
- 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
Nice-to-Haves
- Exposure to platforms like SageMaker, Vertex AI, or Azure ML
- Built products that support AI workflows
Skills
Distributed Systems, Scalable Apis, Cloud Native Infrastructure, Real-Time Serving, ML Infrastructure, Gpu Orchestration, Service-Oriented Architecture, Deployment Pipelines, System Observability, Scala, Go, Python, SageMaker, Vertex Ai, Azure Ml
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