Job Description

Your Opportunity

The AI Enablement Lead - Software Engineering is responsible for establishing and accelerating AI adoption across the software development lifecycle (SDLC) to improve engineering productivity, software quality and delivery outcomes. The role identifies, designs and implements AI-enabled engineering use cases that deliver measurable business value.

The role leads end-to-end delivery of AI capabilities including code graphing, code analysis, code generation, code review, test case generation and intelligent testing, while building organisational capability and embedding modern AI-driven engineering practices across NSW LRS.

Your Responsibilities

• Develop and maintain the AI Software Engineering roadmap, delivery priorities and implementation plans to achieve strategic alignment, measurable outcomes and sustainable adoption of AI within the SDLC.
• Identify, assess and prioritise AI-enabled software engineering use cases to achieve improvements in developer productivity, software quality, delivery speed and engineering effectiveness.
• Lead the design, implementation and optimisation of AI solutions for code graphing, code analysis, code generation, code review, test automation and quality engineering to achieve demonstrable value across the software delivery lifecycle.
• Establish engineering standards, frameworks, patterns and guardrails for AI-assisted software development to achieve secure, consistent and scalable adoption across technology teams.
• Partner with development, business analysis, testing and architecture teams to embed AI capabilities into engineering workflows and delivery practices to achieve improved collaboration and delivery outcomes.
• Deliver AI capability uplift, coaching and knowledge-sharing initiatives for engineering teams to achieve increased proficiency, adoption and effective use of AI-enabled development tools.
• Monitor, evaluate and report on AI engineering outcomes, performance metrics, benefits and risks to achieve continuous improvement, executive visibility and evidence-based decision-making.
• Ensure AI is implemented with appropriate consideration for system and data security within software engineering processes to achieve compliance, risk management and trusted use of AI technologies.
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