Amazon
Principal Technical Program Manager, Sequence Models (project Sequoia)
$177K–$275K
New York, NY +3 · Principal · Full-time · Posted Aug 25, 2026
- Location
- New York, NY
SEATTLE, WA
San Francisco, CA
Palo Alto, CA - Experience
- 7+ years working directly with engineering teams; 7+ years of technical product or program management; 5+ years of software development. Preferred: 8+ years managing complex technology projects.
About the job
Leads planning and delivery of Amazon-wide sequence-model technology programs, aligning engineering, product, science, and business teams to develop scalable models that improve customer journeys and advertising decisions.
What you'll do
- Own end-to-end program execution, roadmap alignment, governance, and executive reporting for cross-organizational technical initiatives.
- Manage technical and operational risks, influence architecture decisions, and drive scalability, reliability, performance, and operational improvements.
- Coordinate senior stakeholders and cross-functional teams; represent the program in executive reviews and mentor other TPMs.
What they ask for
- 7+ years working directly with engineering teams.
- 7+ years of technical product or program management experience.
- 5+ years of software development experience.
- Experience designing or architecting systems; managing cross-functional programs and release schedules; and owning roadmap strategy and definition.
Nice to have
- 8+ years of hands-on experience managing complex technology projects.
- Experience managing cross-functional projects, building sustainable processes, and coordinating release schedules.
Pay
203,500.00 - 275,300.00 USD annually (base salary), Palo Alto; 203,500.00 - 275,300.00 USD annually (base salary), San Francisco; 194,700.00 - 263,400.00 USD annually (base salary), New York; 177,000.00 - 239,400.00 USD annually (base salary), Seattle
Tools
Generative AI, classical ML, Causal Inference, Natural Language Processing, Computer Vision, distributed systems
AI focus
The role drives programs for sequence models that analyze customers’ journeys and support actionable insights, including advertising decisions; the team uses Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision.
Model-written summary · the original posting is authoritative