Senior GenAI Product Manager – SageMaker Platform

Amazon Web Services (AWS); Bellevue (WA); On-site; USD 152,000 - 237,000; Full time

Job summary

Amazon Web Services (AWS) seeks a Senior Product Manager Technical (PMT-ES III) to own product strategy for SageMaker AI and drive the next evolution of how customers build, train, and deploy ML and GenAI models.

You will define the roadmap, prioritize features, and translate complex ML workflows into delightful experiences that help data scientists and ML engineers move faster from idea to production. This role blends strategy with hands-on execution and cross-functional leadership.

Qualifications

• 5+ years of technical product management with internet business experience.
• 5+ years of working as a Technical Product Manager.
• 3+ years of technical experience (software development, network development, IT).
• 7+ years of full product lifecycle experience.
• 5+ years of P&L management and pricing experience.
• 5+ years of creating written docs for development of new products.

Responsibilities

• Define and execute product strategy and roadmap for your product area.
• Drive feature prioritization and launch planning.
• Own P&L reporting and business metrics, tracking adoption, usage, and revenue growth.
• Partner with engineering to define technical requirements and specifications for new features.
• Work with AWS service teams to integrate SageMaker with broader AWS ecosystem.
• Support the go-to-market strategy and drive customer adoption.

Skills

Technical product management

P&L management

Enterprise security experience

Cloud computing experience

Bachelor's degree in CS/Engineering/ET

Education

Bachelor's degree in computer science, engineering, math, finance, or economics

Job description

Amazon Web Services (AWS) seeks a Senior Product Manager Technical (PMT-ES III) to own product strategy for SageMaker AI and drive the next evolution of how customers build, train, and deploy ML and GenAI models.

You will define the roadmap, prioritize features, and translate complex ML workflows into delightful experiences that help data scientists and ML engineers move faster from idea to production. This role blends strategy with hands-on execution and cross-functional leadership.