AI Security Engineer II

• Experience building AI-enabled automation solutions (LLMs, agentic AI, workflow automation)
• Strong programming experience (Python, Java) and integration into CI/CD pipelines
• Experience with IAM, SSO automation, and security workflow optimization

Nice to Have Skills

• Experience with AWS (Bedrock, cloud-native services)
• Exposure to regulated environments (NIST, ISO, SOX, PCI)
• Background in Information Security, specifically IAM
• Experience with policy-as-code and automated control enforcement

Project / Business Initiative

• Build and scale AI-driven security automation within Information Security & Risk (ISR)
• Initial focus on Identity & Access Management (IAM), expanding across ISR teams

Methodology

• Agile / Iterative

Team / Culture

• Newly formed team within Information Security & Risk (ISR)
• High-impact, fast-moving environment focused on innovation and automation
• Strong collaboration across security, engineering, and business teams
• Looking for self-starters who can operate with ambiguity and drive initiatives independently

Industry Experience Required

• Not required, but experience in regulated environments is highly valued

Job Summary

 

The Security Engineer II – AI will play a key role in advancing security operations through AI, automation, and workflow optimization. This individual will partner with security and engineering leaders to identify opportunities, design solutions, and deliver AI-enabled automation that improves efficiency, consistency, and security posture. The role begins with a focus on IAM and expands across broader security domains, emphasizing hands-on development, innovation, and enterprise-scale impact.

Key Responsibilities

• Design, build, and deploy AI-enabled security automation solutions
• Identify and eliminate manual processes through intelligent automation
• Integrate AI workflows into CI/CD pipelines and enterprise systems
• Develop scalable workflows for IAM, SSO provisioning, and application onboarding
• Apply policy-as-code and automated remediation for security and compliance
• Partner with cross-functional teams to translate business needs into technical solutions
• Leverage LLMs and agentic AI to enhance security operations
• Support governance, risk, and data protection initiatives
• Contribute to architecture, design reviews, and technical standards
• Coach and enable teams to adopt AI-driven processes
• Improve speed, auditability, and operational resilience across security teams

Required Qualifications

• Associate’s or Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
• 8+ years of experience in security, engineering, or technology roles
• Hands-on experience building AI-enabled automation solutions end-to-end
• Experience working with LLMs and AI frameworks (including tool/function calling)
• Proven experience building agentic AI solutions
• Experience integrating AI workflows into enterprise engineering environments
• Strong understanding of security operations, governance, and risk
• Strong communication skills with ability to translate business requirements into technical solutions
• Ability to operate in fast-paced, ambiguous environments
• Strong collaboration and stakeholder management skills

Preferred Qualifications

• Experience with AWS (including Bedrock)
• Experience with GitHub and GitHub Copilot
• CI/CD pipeline integration experience
• Experience with IAM and SSO automation
• Experience applying AI in security use cases (anomaly detection, UEBA, automated remediation)
• Experience working in regulated environments and implementing compliance frameworks
• Strong understanding of policy-as-code and automated controls
• Experience contributing to design reviews, architecture discussions, and code reviews
• Strong innovation mindset with ability to drive process improvements

Technical Environment

• Cloud: AWS
• Languages: Python, Java
• Tools: GitHub, GitHub Copilot, Amazon Bedrock
• Focus Areas: AI/LLMs, agentic AI, IAM, CI/CD integration, automation workflows

Ideal Candidate Profile

• Practical AI engineer with a strong automation mindset
• Experience applying AI to real-world business problems (not just experimental use cases)
• Hands-on builder who can also guide teams through adoption
• Strong collaborator across security, engineering, and business teams
• Self-starter who can drive initiatives with minimal oversight
• Adaptable and continuously learning in evolving AI and security landscapes