Amazon Web Services, Inc.
Applied Science, amazon security
SrManager,AppliedScience,AWSCompliance&SecurityAssurance
Neural analysis suggests this role is
optimal for Manager candidates.
“Sr Manager, Applied Science, AWS Compliance & Security Assurance at Amazon Web Services, Inc.. Skills: Automated reasoning, Program analysis, Static analysis, Security assurance. Own science roadmap. Prototype novel analyses”
What You'll Achieve.
Impact security posture; Expand reach; Expand impact
Industry & Context.
Automated reasoning; Program analysis; Security assurance
What They're Looking For.
Must Have
10+ years applied research experience, Master's degree Computer Science, 5+ years technical leadership, Deep expertise static program analysis, Deep expertise abstract interpretation, Deep expertise taint analysis, Deep expertise information-flow security, Deep expertise automated reasoning, Proven track record building analysis tools, Proven track record shipping security tooling
Nice to Have
PhD Computer Science, Experience SAT, Experience SMT, Experience mechanical theorem proving, Experience symbolic simulation, Experience programming language type systems, Experience program analysis, Background application security, Background encryption verification, Background data privacy compliance, Track record translating research to production
What You'll Do.
Prototype novel analyses
Review technical artifacts
Hire applied scientists
Develop applied scientists
Retain applied scientists
Foster scientific rigor
Foster operational excellence
Expand platform integration
Deliver security capabilities
Deliver privacy capabilities
Explore formal verification
Expand language support
Develop analysis techniques
Understand security needs
Translate needs into capabilities
Represent team community
Contribute initiatives
Contribute academic partnerships
How You'll Work.
Team & Collaboration
Security stakeholders; Privacy stakeholders; Compliance stakeholders; Automated reasoning experts; Application security teams; Service teams; AWS AppSec; Privacy Engineering
Communication Scope
Technical presentations
Process & Methodology
Roadmap development
Full Job Description
About the Team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale. Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. About the Role We are looking for an experienced Applied Science Manager to lead the team's static analysis platform science team. In this role, you will own the technical vision and roadmap for our automated reasoning engine's static analysis capabilities, drive innovation in scalable program analysis, and lead a team of applied scientists working at the frontier of automated reasoning for security while also contributing technically as a player/coach. You will partner closely with security, privacy, and compliance stakeholders across AWS to expand the reach and impact of provably correct code analysis. You will also partner closely with automated reasoning experts across the company and contribute to the science of security Key job responsibilities Technical Leadership: Own the science roadmap for our automated reasoning engine, including taint analysis, compositional heap analysis, modular method summarization, and dataflow graph generation Hands-on Contribution: Personally contribute to key research and design decisions, including prototyping novel analyses and reviewing technical artifacts Team Building & Management: Hire, develop, and retain a world-class team of applied scientists; foster a culture of scientific rigor, innovation, and operational excellence Product Integration: Partner with application security and service teams to expand our platform's integration footprint and deliver new security and privacy analysis capabilities Research & Innovation: Advance the state of the art in static program analysis, including exploring formal verification of analysis
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