AI DevSecOps Governance SME - 12 Month Contract

AI DevSecOps Governance SME — 12-Month Contract, Sydney
 
Join a well-established technology services and consulting organisation to pioneer and scale AI-driven security governance across the enterprise software development lifecycle (SDLC).
 
The Role
 
In this forward-looking engineering role, you'll lead the implementation of governance frameworks and security standards powered by AI and Large Language Models (LLMs), integrating intelligent automation directly into CI/CD pipelines to transform how security policies, compliance checks, and code reviews are enforced across enterprise delivery teams.
 
Key Responsibilities

• AI-Driven Security Governance  - Design, implement, and enforce DevSecOps governance frameworks, security guardrails, and compliance standards utilising AI capabilities and LLMs
• Automated Policy Enforcement  - Build and deploy AI-assisted controls for automated code review, policy validation, threat modeling workflows, and security compliance checks within CI/CD pipelines
• Responsible AI & Security Standards  - Establish policy guidelines and security baselines for developer AI usage (AI code assistants, generative models, agentic workflows) to manage data privacy, IP, and code vulnerability risks
• Pipeline Integration & Shift-Left  - Integrate intelligent security testing and automated remediation guidance into modern CI/CD systems (e.g. GitHub Actions, GitLab CI, Azure DevOps)
• Cross-Functional Leadership  - Partner with Security Architecture, Engineering Leads, and Product Teams to define AI governance roadmaps and drive developer adoption across squads

What You'll Bring
 
Essential:

• Deep hands-on experience establishing DevSecOps practices, CI/CD security controls, and application security standards in enterprise environments
• Practical experience using AI/LLM tools to automate security governance, policy checking, or code review workflows - not just theoretical understanding
• Proven ability to translate complex regulatory, security, and data privacy requirements into enforceable, automated software controls
• Proficiency with modern CI/CD platforms, scripting (Python, Bash), and APIs to integrate AI workflows into active pipelines
• Excellent stakeholder management skills with a track record of driving security cultural shifts and developer adoption

Desirable:

• Exposure to secure AI deployment frameworks, model risk management, or AI safety standards (e.g. OWASP Top 10 for LLMs, NIST AI RMF)
• Experience with enterprise code scanning tools (SAST, SCA, DAST) and AI-driven triage mechanisms