Technical Program Manager, AI Data Infra & Systems

Location: Mountain View or Redmond, United States.

Base pay: USD $165,600–$296,400 per year across the U.S.; USD $220,800–$331,200 per year in the San Francisco Bay Area and New York City metropolitan area.

Company

Microsoft AI builds frontier models and products reaching millions of people, from pretraining through post-training, evaluation, and launch.

What you will do

• Own the end-to-end data acquisition operating and governance model across opportunities, contracts, work orders, supplier delivery, inventory, budgets, ingestion, validation, cataloging, and training usage.
• Manage and grow operations, automation, and engineering teams, including technical leads and the engineering function responsible for acquisition infrastructure.
• Own the acquisition platform roadmap, including automated ingestion and validation, supplier metadata capture, publishing pipelines, role-based reporting, and persistent lineage across datasets and model training runs.
• Partner with compliance, infrastructure, platform, finance, legal, research, and external suppliers on governance, access control, retention, disclosure, procurement, and operating priorities.
• Scale supplier operations through onboarding, standardized work orders, delivery requirements, quality and throughput measurement, and contractual quality protections.
• Build a researcher-facing data catalog and improve audit readiness, regulatory compliance, data quality, quality assurance, and procurement cycle time.

Requirements

• Extensive experience leading operations at scale in data operations, supply chain, vendor or supplier management, or procurement operations.
• Experience managing engineering teams and owning a technical roadmap, including build, buy, and partner decisions and direct technical leadership.
• Experience replacing manual, spreadsheet-driven processes with enterprise-wide systems and iterating on platforms.
• Technical fluency in data pipelines, ETL, SQL/Kusto, data warehouses, databases, PostgreSQL, NoSQL databases, ingestion and validation, cloud storage, access control, metadata, and lineage.
• Ability to reason about trade-offs between data coverage, metadata completeness, and operational simplicity.
• Experience operating under data governance, privacy, licensing, regulatory, audit, and disclosure obligations.
• Strong executive communication and ability to align research, engineering, finance, legal, infrastructure, and external suppliers.
• Familiarity with the AI/ML data landscape, including pretraining corpora, multimodal data, post-training, reinforcement-learning task supply, and supplier ecosystems.

Culture & Benefits

• Work closely with research, product, compliance, infrastructure, platform, finance, legal, and external supplier stakeholders.
• Benefits and other compensation may be available depending on role eligibility.
• Applications are accepted on an ongoing basis until the position is filled, with the posting open for at least five days.