As a Staff Engineer at Databricks, you will play a critical role in shaping the product experience and core infrastructure for the Foundation Model Serving API. This position focuses on designing and building systems for high-throughput, low-latency inference on GPU workloads with frontier models. You will collaborate closely with various teams to deliver a world-class foundation model API product. No prior ML or AI experience is necessary, but a strong background in operationally sensitive systems is required.

• 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.

• 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, 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.