Lead Security Engineer - Threat modelling, Cloud Security

Job Responsibilities

• Facilitate security requirements clarification for multiple networks to enable multi-level security that satisfies organizational needs
• Work with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability
• Triage based on risk assessments of various threats and manage resources to cover the impact of disruptive events
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  

Required Qualifications, Capabilities And Skills

• Formal training or certification on security engineering concepts and 5+ years applied experience
• 10+ years cyber security hands-on experience
• Skilled in planning, designing, and implementing enterprise-level security solutions
• Advanced in one or more programming languages
• Advanced knowledge of platform security enablement and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., AWS, Kubernetes, artificial intelligence, machine learning, etc.)
• Extensive experience with threat modeling and business risk articulation
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Ability to tackle design and functionality problems independently with little to no oversight
  

Preferred Qualifications, Capabilities And Skills

• Experience effectively communicating with senior business leaders
  

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