Staff Technical Program Manager – GenAI Ops & Capacity Planning

P-1489

About Databricks

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 medical breakthroughs. We do this by building and operating the world’s best data and AI infrastructure platform so our customers can turn deep data insights into real business impact. Founded by engineers and deeply customer-obsessed, we thrive on solving hard technical challenges, from next-generation data experiences to operating infrastructure at massive global scale. And we’re only getting started. For more information, visit www.databricks.com.

The Role

Databricks is looking for a Staff Technical Program Manager to drive GenAI Operations and Capacity Planning for our large-scale LLM and GPU-backed platform. This role is designed for a senior, hands-on TPM who thrives in technically deep, data-driven environments and enjoys owning complex operational programs end to end.

As a Staff TPM, you will own execution for critical GenAI operational initiatives, operate with significant autonomy, and partner closely with AI/ML engineering, infrastructure, finance, partner ops and cloud/LLM providers. You will use strong analytical skills to guide decisions, surface risks, and continuously improve how Databricks launches, scales, and governs GenAI workloads.

You will report to a Technical Program Leader and operate across multiple time zones in a fast-moving, highly ambiguous environment.

What You’ll Do

GenAI & LLM Operations

• Plan and execute day-0 launches of new LLM models on Databricks, ensuring production readiness across engineering,commercialization,go-to-market, legal and cloud service partners
• Partner with AI/ML and platform engineering teams to operationalize LLM onboarding, rollout, and lifecycle management.
• Define and maintain launch checklists, operational runbooks, and success metrics for GenAI workloads.

GPU & LLM Capacity Planning

• Own GPU and LLM capacity planning, forecasting, and allocation for GenAI workloads.
• Build and maintain SQL-driven analytical models and dashboards to forecast demand, track utilization, and surface capacity risks.
• Balance customer demand, growth trajectories, and contractual commitments to inform short- and medium-term capacity decisions.

Utilization, Efficiency & Analytics

• Track and drive efficient consumption of GPU and LLM capacity, identifying underutilization, contention, and inefficiencies.
• Define and monitor KPIs for utilization, efficiency, and reliability of GenAI platforms.
• Use data to recommend improvements to engineering roadmaps, operational processes, and cost optimization efforts.

Governance, Controls & Reporting

• Execute governance mechanisms to ensure GenAI capacity usage aligns with contractual, financial, and compliance requirements.
• Produce clear, data-backed reporting for senior leaders on capacity health, utilization trends, and operational risks.
• Generate consumption reports, usage metrics reporting and share of wallet attestations
• Ensure documentation, controls, and processes are audit-ready and consistently followed.

What We Look For

Minimum Qualifications

• 10+ years of overall industry experience, including 7+ years in Technical Program Management.
• Experience leading cross-functional GenAI, AI/ML, or infrastructure programs from planning through launch and steady-state operations.
• Strong background in capacity planning, forecasting, and infrastructure analytics.
• Advanced SQL skills and hands-on experience building analytics, dashboards, and operational reporting.
• Ability to translate complex data into clear insights and recommendations for engineering and leadership stakeholders.
• Hands-on experience with at least one major cloud provider: AWS, Azure, or GCP.
• Familiarity with agile methodologies and program management tools such as Jira.
• Comfortable managing ambiguity, driving execution, and handling escalations when needed.

Preferred Qualifications

• Master’s degree or advanced technical degree.
• Experience operating LLM, GPU, or GenAI platforms in production environments.
• Background in cloud infrastructure, distributed systems, or platform engineering.
• Previous software or hardware development experience.

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow. Follow Databricks on Twitter, LinkedIn, and Facebook to learn more.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We ensure our hiring practices meet equal employment opportunity standards and consider candidates without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical or mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, or other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within the Employer’s discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Pay Range Transparency

Databricks is committed to fair compensation practices. The pay range(s) for this role is listed below and represents base 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 uses 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 about which range your location is in visit our page here.