support Woodside's global operations and our role in the energy transition.
Founded in 1954, Woodside established the liquefied natural gas (LNG) industry in
Australia 40 years ago and supplies customers around the globe. 70 years on,
Woodside continues to be driven by a spirit of innovation and determination.
At Woodside, we know great results come from our people feeling valued, getting the
support they need to reach their full potential and working in a psychologically and
physically safe work environment. We believe in nurturing talent and providing
opportunities for continuous learning and career advancement.
Refer to our corporate website for more information about our different locations and
projects: 
About Woodside Global Solutions
Woodside Global Solutions in Bengaluru is being built as a hub of excellence, to drive
innovation, digital transformation, and global collaboration.
Working as one Global team, the Woodside Digital team is a trusted partner driving
transformation within the organisation. We are bold in our ambitions and resolute in
our actions. Through cutting-edge AI, robust cyber security, and advanced data
solutions we drive innovation and influence every part of our business.
We are looking for talented professionals who are passionate about technology and
eager to make a global impact, helping to shape the future of Woodside together.
 

PURPOSE

The L3 Governance Analyst is a key role within the AI and Analytics team, responsible for establishing, operationalising, and continuously improving AI governance practices across the enterprise. The role ensures that AI systems are developed, deployed, and operated in a manner that is ethical, secure, compliant, and aligned with organisational risk appetite, regulatory obligations, and enterprise standards.

Working closely with AI product teams, cyber security, legal, privacy, risk, and business stakeholders, the AI Governance Specialist provides pragmatic governance guidance that enables responsible AI innovation at scale. The role balances policy and control design with hands-on enablement, ensuring governance is embedded into AI delivery lifecycle processes rather than treated as an afterthought.

 

REPORTING

To: Architecture & Governance Lead

Reports: None

 

RESPONSIBILITIES AND ACCOUNTABILITIES

AI Lifecycle Oversight

• Embed governance controls across the end-to-end AI lifecycle, including ideation, design, development, deployment, monitoring, and retirement.
• Support AI use case intake, triage, and risk classification processes.
• Define governance checkpoints and assurance activities proportionate to AI risk and materiality.

Risk, Compliance & Assurance

• Identify, assess, and manage AI-related risks, including bias, explainability, robustness, security, data misuse, and third-party dependencies.
• Support AI risk assessments, control attestations, and internal/external audits as required.
• Partner with Cyber Security, Privacy, Legal, and Risk teams to resolve AI-related control gaps and issues.

Policy, Process & Enablement

• Develop clear guidance, templates, and playbooks to support compliant and responsible AI delivery.
• Enable AI teams through practical advice on governance-by-design, rather than gatekeeping.
• Contribute to training and awareness initiatives to uplift AI governance literacy across technical and non-technical stakeholders.

Tooling & Observability

• Implement observability tools for tracing, logging, and performance monitoring.
• Ensure robust API testing and authentication flows across service layers.

Monitoring & Continuous Improvement

• Define metrics and indicators to monitor AI governance effectiveness and compliance.
• Support post-deployment monitoring of AI systems, including model drift, performance, and risk signals.
• Continuously improve governance practices based on lessons learned, incidents, and emerging regulatory or technology trends.
• Stakeholder Engagement & Collaboration
• Act as a trusted advisor to AI product teams, platform teams, and business stakeholders.
• Engage with enterprise governance forums and councils to represent AI governance perspectives.
• Clearly communicate governance expectations, risks, and trade-offs to both technical and non-technical audiences.

SKILLS & EXPERIENCE

Technical Skills / Experience:

• Bachelor’s degree in Information Technology, Engineering (Computer Science), Data Science, Risk, Law, or a related discipline.
• 5+ years of experience in technology governance, risk management, compliance, or AI/analytics-related roles.
• Strong understanding of AI/ML concepts, including Generative AI, model lifecycle management, and data dependencies (hands-on development experience beneficial but not mandatory).
• Experience working with governance domains such as cyber security, privacy, data governance, or model risk management.
• Familiarity with Responsible AI principles, ethical AI frameworks, and emerging AI regulations.
• Ability to translate complex technical and regulatory concepts into clear, practical guidance.
• Strong stakeholder management, facilitation, and communication skills.
• Experience working in agile, product-based digital delivery environments.

 

 

 

 

 

 

 

 

 

KEY INTERACTIONS

Internal:

• AI and Analytics delivery teams
• AI Platform and Engineering teams
• Cyber Security and Architecture
• Legal, Privacy, Risk, and Compliance
• Digital and Business stakeholders

External:

• AI vendors
• External auditors or advisors (as required)

 

experience

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