Sr. Manager, Engineering - Model Serving

San Francisco, California Apply now RDQ127R51 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. Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency. As a Senior Engineering Manager, you will lead the team owning both the product experience and the foundational infrastructure of Model Serving — shaping customer-facing capabilities while designing for scalability, extensibility, and performance across both CPU and GPU inference — and collaborate closely across the platform, product, infrastructure, and research organizations. The impact you will have:

• Lead, mentor, and grow a high-performing engineering team responsible for both the customer-facing Model Serving product and its foundational infrastructure — covering runtime, APIs, scaling, reliability, and integrations.
• Define and own the product and technical roadmap for Model Serving, balancing customer experience, functionality, and foundational investments across deployment, inference, monitoring, and scaling.
• Collaborate closely with product, research, platform, and infrastructure teams to drive end-to-end delivery — from ideation and prioritization to launch and operation.
• Ensure Model Serving meets stringent SLAs, SLOs, and performance and reliability goals, continuously improving operational efficiency and customer experience.
• Drive architectural decisions and product design around latency, throughput, autoscaling, GPU/CPU placement, and cost optimization.
• Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.
• Promote best practices in code quality, testing, observability, and operational readiness.
• Foster a culture of excellence, inclusion, and continuous improvement across the team.
• Partner with recruiting to attract,...