Amazon
Principal PM-T, Customer Success Intelligence Team , AWS Specialist and Partner Organization
$180K–$280K
Seattle, WA +2 · Principal · Full-time · Posted Aug 19, 2026
- Location
- Seattle, WA
Mountain View, CA
San Francisco, CA - Experience
- 7+ years of technical product management, program management or engineering experience.
- Education
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience.
About the job
Owns the product lifecycle for AWS Customer Success Intelligence tools that use customer data, predictive models, and intelligent agents to identify risks, recommend interventions, and improve post-deployment customer outcomes.
What you'll do
- Set product vision and roadmap; translate customer, field, and partner needs into product and technical requirements.
- Design data, scoring, and workflow automation architectures, and work with engineering teams on priorities and delivery.
- Run beta testing and launches, measure product and customer outcomes, and coordinate across AWS teams and launch compliance gates.
What they ask for
- Experience owning and driving product roadmap strategy and definition.
- Experience writing PRDs, technical specifications, and business requirements documents.
- Experience designing system architectures or defining technical requirements for distributed systems.
- Experience with sprint planning, backlog prioritization, and agile development processes.
Nice to have
- Experience building products incorporating ML models, agentic systems, or applied AI in production.
- Experience with customer success, post-launch adoption, or customer health platforms at enterprise scale.
Pay
206,900.00 - 279,900.00 USD annually (base salary); 206,900.00 - 279,900.00 USD annually (base salary); 179,900.00 - 243,400.00 USD annually (base salary)
Tools
ML, PRFAQs, distributed systems, agile
AI focus
Builds AI-powered systems and agent-based workflows to surface customer risk, recommend interventions, automate workflows, and accelerate customer outcomes; includes ML-driven scoring and measuring model performance.
Model-written summary · the original posting is authoritative