At Databricks, we are passionate about enabling data 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.

Foundation Model Serving is the API Product for hosting and serving frontier AI model inference for open source models like Llama, Qwen, and GPT OSS as well as proprietary models like Claude and OpenAI GPT. For this role, no prior ML or AI experience is necessary. We’re looking for engineers who have owned high scale operational sensitive systems like customer facing APIs, Edge Gateways, ML Inference, or similar services and have an interest in getting deep building LLM APIs and runtimes at scale.

As a Staff Engineer, you’ll play a critical role in shaping both the product experience and core infrastructure. You will design and build systems that enable high-throughput, low-latency inference on GPU workloads with frontier models, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class foundation model API product.

The impact you will have:

Design and implement core systems and APIs that power Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.
Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.
Contribute directly to key components across the serving infrastructure — from working in systems like vLLM and SGLang to creating token based rate limiters and optimizers — ensuring smooth and efficient operations at scale.
Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What we look for:

10+ years of experience building and operating large-scale distributed systems.
Experience leading high-scale operationally sensitive backend systems.
A track record of up-leveling teams engineering excellence.
Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
Strong communication skills and ability to collaborate across teams in fast-moving environments.
Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
Passion for mentoring, growing engineers, and fostering technical excellence.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page he

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