Sr. Staff Technical Program Manager - GenAI

Databricks
Mountain View, California; San Francisco, CaliforniaPosted 4 March 2026

Job Description

<p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">P-1489</span></p> <h2><strong>About Databricks</strong></h2> <p><span style="font-size: 12pt;">At Databricks, we are passionate about empowering data teams to tackle the world's most complex challenges — from bringing the next mode of transportation to reality to accelerating the development of medical breakthroughs. We achieve this by building and operating the world's best data and AI infrastructure platform, enabling our customers to leverage deep data insights and enhance their business.</span></p> <p><strong>Shape the Future of AI at Scale</strong></p> <p>Join Databricks' GenAI team to help build the Data Intelligence Platform that combines the best of data warehouses and data lakes while making generative AI real for enterprises. This is your opportunity to drive mission-critical programs that will define how organizations build, deploy, and scale AI applications.</p> <p><strong>The Impact You'll Make:</strong></p> <p>As a Sr. Staff Technical Program Manager in our GenAI org, you'll be the orchestrator of breakthrough AI capabilities reaching millions of users. You'll drive the successful delivery of cutting-edge GenAI products - from vector databases and model serving infrastructure to Agent Bricks. Your work will directly enable our customers to move from AI experimentation to production at unprecedented scale.</p> <p><strong>What You'll Own:</strong></p> <ul> <li><strong>Priority Product Launches</strong>: Lead cross-functional execution of high-visibility GenAI features</li> <li><strong>Scalable Operations</strong>: Navigate complex technical challenges at the intersection of distributed systems, ML infrastructure, and product requirements. Design and implement processes that enable our platform to serve at scale </li> <li><strong>GTM Customer Adoption: </strong>Partner with field teams, solution architects, customer success, marketing and other XFN teams to drive enterprise adoption of our GenAI offerings - from defining adoption metrics and success criteria to managing early access programs, building customer feedback loops, and ensuring smooth production rollouts </li> <li><strong>Engineering and product Excellence</strong>: Partner with PM and Engineering leaders to translate customer needs into technical requirements, ensuring our GenAI platform delivers both cutting-edge capabilities and enterprise-grade reliability</li> <li><strong>GenAI powered operations</strong>: Leverage automation and GenAI tools to scale the team’s operations and support rapid experimentation and deployment of emerging AI technologies</li> </ul> <p><strong>What We're Looking For:</strong></p> <ul> <li>10+ years driving <strong>high-complexity, business-critical technical programs</strong> across ML/AI, large-scale distributed systems, or cloud infrastructure.</li> <li>Proven ability to <strong>own an entire program area end-to-end</strong>, scaling it from 0→1 or evolving it to the next stage of adoption, with direct measurable business impact.</li> <li>Excellence in <strong>structuring and driving clarity in ambiguous problem spaces</strong>, shaping strategy with engineering and product leaders, and aligning across multiple teams/orgs.</li> <li>Track record of <strong>leading large scale cross-functional programs</strong>, proactively surfacing risks, creating new processes, and ensuring on-time delivery of critical launches.</li> <li>Strong <strong>executive communication skills</strong>: concise written and verbal updates, ability to facilitate alignment across VPs/Directors, and polished presentations to senior leadership.</li> <li>Expertise in <strong>data-driven decision making</strong>: defining success metrics, building dashboards, and using SQL/Python/notebooks to ground decisions in analysis.</li> <li>Ability to act as a <strong>force multiplier</strong>: mentoring other TPMs, introducing scalable processes, and driving organizational efficiency at th ... (truncated, view full listing at source)