Senior Technical Program Manager, Productivity Engineering (Data Platform · AI Transformation)

About the role

10x Genomics is rewriting the rules of biological discovery - and our platform needs to move as fast as our science. We are building a modern, AI-first technology stack, and this role sits at the center of it. We are looking for a Senior TPM who thrives in ambiguity, builds the plan rather than inherits one, and understands that data programs are not just delivery work - they are the foundation that makes AI possible. You will own the roadmap across our AI / Data Platform and integration programs, and you will expand your scope as the org scales. You have operated in environments where the process did not exist yet - and you built it. You do not wait for a fully-defined charter. You are energized by a flat org, a direct reporting line to leadership, and the expectation that you own outcomes end-to-end.

Responsibilities

• Program Ownership & Delivery
• Own and drive the roadmap across AI / Data Platform and Finance integration programs; expand scope as the business grows.
• Take programs from zero to shipped - scoping, sequencing, dependency management, risk visibility, and retrospective.
• Translate ambiguous business problems into structured, time-bound programs with clear milestones and decision points.
• Run delivery end-to-end without needing a playbook handed to you. You write the playbook.
• Hold engineering, product, and business teams accountable to commitments - without relying on hierarchy to do it.
• AI-First Thinking
• Understand how Data Platform programs create upstream capability for AI and ML - design with that lens from day one.
• Own AI-specific program tracks: NLQ rollout, Bedrock integrations, model deployment pipelines, and data readiness for AI.
• Partner with Data Engineering, Product, and Science teams to ensure programs are not just delivered but compound into AI readiness.
• Push teams to think end-to-end: what does this program unlock downstream, and are we building toward that?
• Represent the AI program portfolio to senior leadership with clarity on status, risks, and strategic trajectory.
• Finance & Application Integrations
• Own delivery of modernized integration programs - ensuring cross-application flows (ERP, CRM, supply chain) work reliably on a modern tech stack.
• Drive the retirement of fragile legacy middleware and the adoption of event-driven, scalable integration patterns.
• Partner with Finance, Operations, and Engineering to translate business process requirements into well-architected integration programs.
• Ensure tax, order management, procurement, and revenue-impacting workflows have zero-tolerance reliability standards.
• Define the integration roadmap in partnership with architects and engineering leads - own it, defend it, and ship it.
• Leadership & Communication
• Operate effectively in a flat org: influence without hierarchy, build alignment without bureaucracy.
• Be the connective tissue across Engineering, Product, Finance, and Operations - translate technical complexity into business impact.
• Identify cross-program risks before they become incidents. Escalate with a proposed solution, not just a flag.
• Minimum Requirements
• 5+ years of TPM experience with demonstrated ownership of complex, multi-stakeholder programs.
• Meaningful time at a mid-stage startup (Series A-D), or equivalent experience as a founder or early employee - you know what it means to build without a safety net.
• Hands-on delivery across data infrastructure or data platform programs: pipelines, warehousing, ELT, real-time data flows.
• Fluency in modern integration patterns - you can hold a substantive conversation with engineers about event-driven architecture, API design, and middleware retirement without needing a glossary.
• Proven ability to build the roadmap, not inherit one. You have done this before and have the scars to show it.
• Strong written and verbal communication - you can write a crisp exec update and a detailed program brief and know when each is appropriate.
• Preferred Skills and Experience
• Experience driving AI or ML programs: NLQ, model deployment pipelines, feature stores, or GenAI product integrations.
• Familiarity with the 10x stack or equivalent: Snowflake, Airflow, Kafka, dbt, AWS, Oracle Fusion.
• Background in life sciences, genomics, or regulated data environments.
• Worked cross-functionally across Engineering, Product, Finance, and Operations simultaneously - not sequentially.
• Pay Range
• $164,100 - $222,100 USD

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