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Technical Program Manager - GenAI Ops & Capacity Planning

Job in Seattle, King County, Washington, 98127, USA
Listing for: Menlo Ventures
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    AI Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Staff Technical Program Manager - GenAI Ops & Capacity Planning

P-1489

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, Linked In, and Facebook to learn more.

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 DoGenAI & 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 under utilization, 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.
Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the…

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