Sr. Product Manager Technical , Secrets Management

Amazon Amazon · Big Tech · Seattle, WA · Project/Program/Product Management--Technical

This role is for a Senior Product Manager Technical focused on AI-driven security innovation within AWS Secrets Management. The core responsibility is to define and execute the product strategy for AI-powered secrets management, including intelligent credential rotation, anomaly detection, automated remediation, and generative AI integrations. The role also involves shaping the security posture for AI/ML workloads, securing credentials for AI agents and pipelines, and building AI-native developer experiences. It requires understanding customer needs, driving cross-functional influence, making business decisions, and collaborating with engineering to launch new features.

What you'd actually do

  1. Drive AI-first product strategy — Define and execute the vision for AI-powered secrets management, including intelligent credential rotation, AI-driven anomaly detection, automated remediation workflows, and generative AI integrations that simplify security for developers.
  2. Shape AI security posture — Identify and address the unique security challenges that AI and machine learning workloads introduce — securing model credentials, managing secrets for AI agents and autonomous pipelines, and ensuring AI systems themselves don't become vectors for credential exposure.
  3. Build AI-native developer experiences — Leverage generative AI to eliminate friction in secrets management workflows — from natural-language policy creation to AI-assisted troubleshooting and intelligent secret discovery.
  4. Own product strategy and roadmap — Develop and drive the AWS Secrets Manager product strategy, translating customer needs and market trends into creative, high-quality, simple features that accelerate adoption.
  5. Deeply understand customers — Engage with customers regularly through calls, visits, customer briefings, advisory boards, and travel to conferences, summits, and customer sites to understand their secrets management challenges inside and out.

Skills

Required

  • Product strategy and roadmap development
  • Customer engagement and understanding
  • Cross-functional leadership and influence
  • Business decision-making (pricing, prioritization)
  • Collaboration with engineering teams
  • Launch and go-to-market planning
  • Practical cryptography
  • Application security
  • AI-driven security innovation

Nice to have

  • Experience with generative AI integrations
  • Experience with AI agents and autonomous pipelines
  • Experience with ML pipelines
  • Experience with secrets management at scale
  • Experience with cloud security services

What the JD emphasized

  • AI-first organization
  • AI-driven security innovation
  • securing credentials for AI agents, ML pipelines, and model inference
  • AI and machine learning workloads

Other signals

  • AI-first organization
  • generative AI and machine learning to reimagine how secrets are managed
  • AI-powered threat detection
  • intelligent credential lifecycle automation
  • securing credentials for AI agents, ML pipelines, and model inference