Manager Iii, Software Development, Ecat Team, Security Assurance Engineering (sae)

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Manager III, Software Development for Amazon's Security Assurance Engineering (SAE) team, focusing on building AI-powered compliance and security tools. The role involves leading a team to develop intelligent automation systems using ML and NLP for cloud security and compliance, including intelligent document processing and AI/ML-driven workflows. The position requires defining strategic vision, making architectural decisions, and partnering with stakeholders to translate regulatory requirements into engineering solutions.

What you'd actually do

  1. Lead, develop, and inspire a talented team of engineers building AI/ML-powered compliance and security automation tools, providing mentorship, career growth opportunities, and creating an inclusive team environment
  2. Define and execute strategic roadmaps by working backwards from customer problems, owning team charter, vision, tenets, and long-term architectural decisions that influence organizational goals
  3. Drive architecture, design, and delivery of intelligent document processing systems leveraging NLP, machine learning models, and generative AI to automate compliance workflows at scale
  4. Own operational excellence for security-critical systems handling sensitive data, including incident response, security reviews, and maintaining the highest standards for data protection and privacy
  5. Partner with engineering, legal, science, and security teams to identify opportunities for AI/GenAI innovation, evaluate emerging technologies, and integrate them into the team's product roadmap

Skills

Required

  • Leadership experience
  • Experience building and operating software systems
  • Experience with machine learning, natural language processing, and generative AI
  • Experience with cloud-native architectures
  • Experience with security and compliance domains
  • Experience defining strategic vision and roadmaps
  • Experience with architectural design and decision-making
  • Experience managing cross-team dependencies
  • Experience with incident response and data protection

Nice to have

  • Experience in regulated environments
  • Experience with distributed systems design
  • Experience with ML model training and deployment

What the JD emphasized

  • AI-powered compliance and security tools
  • intelligent automation systems
  • machine learning, natural language processing
  • cloud security
  • compliance infrastructure
  • intelligent document processing systems
  • AI/ML-driven workflows
  • data governance processes
  • customer trust
  • regulatory requirements
  • AI/ML and security compliance
  • ambiguous problem spaces
  • intelligent document processing
  • NLP, machine learning models, and generative AI
  • compliance workflows
  • security-critical systems
  • data protection and privacy
  • AI/GenAI innovation
  • ML model training and deployment
  • distributed systems design
  • cloud infrastructure modernization

Other signals

  • AI-powered compliance and security tools
  • intelligent automation systems
  • machine learning, natural language processing
  • intelligent document processing systems
  • AI/ML-driven workflows
  • generative AI
  • AI/GenAI innovation