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

About this role

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.

What You Will Own

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.