Principal Applied Scientist, Secure Work Enablement

## Responsibilities - Set the scientific vision and long-term research agenda: Define what "best-in-class agentic troubleshooting" looks like scientifically, identify the key unsolved problems, and chart a multi-year path to solving them — securing buy-in from VP-level leadership. - Deliver breakthrough solutions on highly ambiguous problems: Independently identify, frame, and solve novel research challenges in agentic AI for troubleshooting — problems where neither the approach nor the success criteria are pre-defined. - Influence and align across the organization: Drive scientific alignment across product, engineering, and business teams. Translate complex ML concepts into actionable product strategy. Represent the science team in leadership forums and planning cycles. - Build and elevate scientific excellence: Mentor scientists and engineers across the team. Establish best practices for experimentation, evaluation, and deployment of agentic systems. Set the standard for scientific rigor and code quality. - Deliver end-to-end production systems with outsized business impact: Own the full lifecycle from research to deployment for Advisor's core intelligence — making pragmatic trade-offs between long-term invention and near-term delivery while ensuring measurable customer and business outcomes. - Advance the state of the art: Contribute to the external scientific community through publications, patents, and engagement that positions AWS as a leader in autonomous AI operations — bringing outside-in innovation back into Advisor. ## Requirements - 5+ years of hands-on work in predictive modeling and analysis experience - PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field - Experience working in predictive modeling and analysis - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Experience programming in Java, C++, Python or related language - Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment ## Nice to Have - 10+ years of relevant work in industry or academia experience - Knowledge of problem solving, algorithm design and complexity analysis - Experience creating novel algorithms and advancing the state of the art - Have peer-reviewed scientific contributions in premier journals and conferences ## Benefits - Influence the broader organization's AI strategy by identifying opportunities to extend Advisor's agentic patterns to adjacent problem spaces, and by publishing findings that advance the state of the art in autonomous IT operations. - Work on cutting-edge agentic AI systems that transform enterprise workspace management through autonomous troubleshooting and self-healing capabilities. - Collaborate with cross-functional teams to shape the future of intelligent, cloud-powered applications that solve enduring business challenges. - Be part of a mission-driven team focused on delivering intuitive, differentiated technology that is easy to adopt and built to scale. - Contribute to the external scientific community through publications, patents, and engagement that positions AWS as a leader in autonomous AI operations.