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

About this role

<h1><strong>About the Role</strong></h1> <p>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.</p> <p>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.</p> <p>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.</p> <h1><strong>What You Will Own</strong></h1> <h2><strong>Program Ownership & Delivery</strong></h2> <ul> <li>  Own and drive the roadmap across AI / Data Platform and Finance integration programs; expand scope as the business grows.</li> <li>  Take programs from zero to shipped — scoping, sequencing, dependency management, risk visibility, and retrospective.</li> <li>  Translate ambiguous business problems into structured, time-bound programs with clear milestones and decision points.</li> <li>  Run delivery end-to-end without needing a playbook handed to you. You write the playbook.</li> <li>  Hold engineering, product, and business teams accountable to commitments — without relying on hierarchy to do it.</li> </ul> <h2><strong>AI-First Thinking</strong></h2> <ul> <li>  Understand how Data Platform programs create upstream capability for AI and ML — design with that lens from day one.</li> <li>  Own AI-specific program tracks: NLQ rollout, Bedrock integrations, model deployment pipelines, and data readiness for AI.</li> <li>  Partner with Data Engineering, Product, and Science teams to ensure programs are not just delivered but compound into AI readiness.</li> <li>  Push teams to think end-to-end: what does this program unlock downstream, and are we building toward that?</li> <li>  Represent the AI program portfolio to senior leadership with clarity on status, risks, and strategic trajectory.</li> </ul> <h2><strong>Finance & Application Integrations</strong></h2> <ul> <li>  Own delivery of modernized integration programs — ensuring cross-application flows (ERP, CRM, supply chain) work reliably on a modern tech stack.</li> <li>  Drive the retirement of fragile legacy middleware and the adoption of event-driven, scalable integration patterns.</li> <li>  Partner with Finance, Operations, and Engineering to translate business process requirements into well-architected integration programs.</li> <li>  Ensure tax, order management, procurement, and revenue-impacting workflows have zero-tolerance reliability standards.</li> <li>  Define the integration roadmap in partnership with architects and engineering leads — own it, defend it, and ship it.</li> </ul> <h2><strong>Leadership & Communication</strong></h2> <ul> <li>  Operate effectively in a flat org: influence without hierarchy, build alignment without bureaucracy.</li> <li>  Be the connective tissue across Engineering, Product, Finance, and Operations — translate technical complexity into business impact.</li> <li>  Identify cross-program risks before they become incidents. Escalate with a proposed solution, not just a flag.</li> </ul> <h2><strong>Minimum Requirements</strong></h2> <ul> <li>  5+ years of TPM experience with demonstrated ownership of complex, multi-stakeholder programs.</li> <li>  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.</li> <li>  Hands-on delivery across data infrastructure or data platform programs: pipelines, warehousing, ELT, real-time data flows.</li> <li>  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.</li> <li>  Proven ability to build the roadmap, not inherit one. You have done this before and have the scars to show it.</li> <li>  Strong written and verbal communication — you can write a crisp exec update and a detailed program brief and know when each is appropriate.</li> </ul> <h2><strong>Preferred Skills and Experience</strong></h2> <ul> <li>  Experience driving AI or ML programs: NLQ, model deployment pipelines, feature stores, or GenAI product integrations.</li> <li>  Familiarity with the 10x stack or equivalent: Snowflake, Airflow, Kafka, dbt, AWS, Oracle Fusion.</li> <li>  Background in life sciences, genomics, or regulated data environments.</li> <li>  Worked cross-functionally across Engineering, Product, Finance, and Operations simultaneously — not sequentially.</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div…