AI DevSecOps Governance SME - Permanent or Contract

We are seeking an experienced AI DevSecOps Governance SME for an initial 12-month contract in Sydney to pioneer and scale AI-driven security governance across our enterprise software development lifecycle (SDLC).
In this forward-looking engineering role, you will lead the implementation of governance frameworks and security standards powered by Artificial Intelligence and Large Language Models (LLMs). You will be responsible for integrating intelligent automation directly into CI/CD pipelines—transforming 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 utilizing 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 (e.g., AI code assistants, generative models, and agentic workflows) to manage data privacy, IP, and code vulnerability risks.
Pipeline Integration & Shift-Left: Integrate intelligent security testing and automated remediation guidance seamlessly into modern CI/CD systems (e.g., GitHub Actions, GitLab CI, Azure DevOps).
Cross-Functional Leadership: Partner closely with Security Architecture, Engineering Leads, and Product Teams to define AI governance roadmaps and drive developer adoption across squads.
Essential Experience:
DevSecOps & AppSec Foundation: Deep hands-on experience establishing DevSecOps practices, CI/CD security controls, and application security standards in enterprise environments.
AI & LLM Implementation: Practical experience using AI/LLM tools to automate security governance, policy checking, or code review workflows (not just theoretical understanding).
Governance & Compliance: Proven ability to translate complex regulatory, security, and data privacy requirements into enforceable, automated software controls.
Pipeline Tooling & Automation: Proficiency with modern CI/CD platforms, scripting (Python, Bash), and APIs to integrate AI workflows into active pipelines.
Communication & Engagement: 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.

Skills
Python, Git, Azure, CI/CD, Artificial Intelligence, LLM, Risk Management

Employment type
Full-time

Work arrangement
Hybrid