Overview In this role you shape the scientific direction of WorkSpaces Advisor, an agentic AI system for proactive workspace troubleshooting. You will set the research agenda, build autonomous reasoning and planning capabilities, and drive continuous learning to improve diagnostics and remediation. You'll lead cross-functional collaboration to translate ML advances into scalable enterprise solutions, maintaining trust and safety in automated actions. This is a hands-on leadership role with impact on product, platform, and AI strategy at AWS.
Responsibilities- Define the long-term scientific vision and multi-year roadmap for agentic troubleshooting
- Deliver breakthrough solutions to ambiguous AI problems in troubleshooting domains
- Align science with product, engineering, and business teams and represent science in leadership forums
- Build and elevate scientific excellence through mentorship and best practices
- Deliver end-to-end production systems for Advisor's core intelligence and measure business outcomes
- Advance the state of the art via external publications, patents, and industry engagement
Key requirements- PhD in a technical field (EE, CS, Math)
- 5+ years of hands-on predictive modeling and analysis
- Experience distilling customer requirements into problem definitions amid ambiguity
- Proficiency in Java, C++, Python or related languages
- Experience leading scientists and mentoring juniors to career growth
- Experience solving problems in agentic AI, planning, or autonomous systems (preferred)
- Knowledge of problem solving, algorithm design and complexity (preferred)
- Peer-reviewed scientific contributions (preferred)
- Strong leadership and mentorship
- Ability to translate complex ML concepts into product strategy
- Cross-functional collaboration and stakeholder alignment
- Predictive modeling and analysis
- Agentic reasoning and autonomous troubleshooting
- Planning and orchestration frameworks
