Chapter Lead - Responsible AI, Agentic AI

Commonwealth Bank of Australia; Sydney; Hybrid; AUD 180,000 - 240,000; Full time

Job summary

Commonwealth Bank of Australia seeks a Chapter Lead to steer Responsible AI capabilities across evaluation, runtime assurance and ongoing monitoring. You will lead a specialist data science chapter, shaping technical direction and delivering scalable AI capabilities across the Group.

You will work hands-on to move ideas from concept to build, test and delivery, enabling AI developers across the Group to implement Responsible AI at scale while partnering with risk, policy, engineering and data

Qualifications

• Proven experience leading teams or significant technical leadership across ML initiatives.
• Strong foundation in statistics, probability and machine learning with ability to interpret model behaviour.
• Hands-on experience designing, developing and evaluating production AI/ML solutions including LLMs, NLP or conversational AI.
• Practical knowledge of cloud environments such as AWS or Azure, version control, CI/CD, containerization, monitoring and observability.

Responsibilities

• Lead and develop a team of data scientists through coaching, knowledge sharing, technical guidance and collaboration.
• Lead the design, development and implementation of evaluation and assurance capabilities for Generative and Agentic AI across the Group.
• Partner with engineering, data science, risk and policy teams to design and deliver Responsible AI capabilities.
• Partner with risk and policy teams to build and operate formal risk controls for responsible AI practices.
• Establish executive risk reporting for responsible AI outcomes to senior leadership.
• Apply statistical methods and structured problem solving to complex challenges in Responsible AI.
• Work with data scientists and developers to gather requirements and identify enhancement opportunities.
• Keep up to date with industry developments in Generative/Agentic AI and responsible AI.

Skills

Team leadership

Statistics

Machine Learning

Python

SQL

Cloud (AWS/Azure)

CI/CD

Containerization

Monitoring/Observability

Communication

Stakeholder influence

Data Science

Education

Tertiary qualification in Data Science/Statistics/CS/Engineering/Math

Tools

SQL

Job description

Chapter Lead - Responsible AI, Agentic AI

Scale advanced Responsible AI capabilities across evaluations, runtime assurance and ongoing monitoring, and embed them in processes and risk controls

Solve complex challenges to influence high-priority initiatives that drive Responsible AI across the Group

Lead a data science team and work with risk and engineering tech teams to build, deploy and manage Responsible AI capability

Do work that matters

At CommBank, we are investing in AI to create better customer experiences and meaningful value for the communities we serve. Within the Responsible AI Domain, advanced data science and risk management come together to set the direction for Responsible AI across the Group.

As Chapter Lead Responsible AI you will lead a specialist chapter of data scientists working across Generative AI, agentic AI and machine learning. You will shape technical direction and deliver capabilities that are used across the Group, guide architecture and design decisions, strengthen delivery practices, and grow the capability of the team.

This is a hands-on leadership role. You will help move ideas from ambiguity through to build, testing and delivery to give AI developers across the Group the tools they need to put Responsible AI into practise at scale.

You will join a highly technical data science team developing and managing key Responsible AI capabilities across evaluations, runtime assurance and ongoing monitoring. The team works closely with risk and policy teams, data scientists from across the Group, engineering teams and others to ensure Responsible AI is built-in and operating seamlessly and at scale.

We value curiosity, pragmatism, inclusion and continuous improvement. We share knowledge, test emerging methods thoughtfully and maintain a strong focus on outcomes and technical quality.

We support flexible ways of working, with a balance between time in the office and remote work. Talk to us about arrangements that work for you.

Key Responsibilities

• Lead and develop a team of data scientists through coaching, knowledge sharing, technical guidance and collaboration
• Lead the design, development and implementation of world-class evaluation and assurance capabilities for Generative and Agentic AI that support data scientists across the Group
• Partner with engineering, data science, risk and policy teams in designing and delivering Responsible AI capabilities
• Partner with risk and policy teams also in building and operating formal risk controls which formalise and standardise responsible AI practises
• Establish executive risk reporting which gives appropriate visibility of responsible AI outcomes to senior leadership
• Apply statistical methods and structured problem solving to complex and ambiguous challenges in Responsible AI
• Work closely with data scientists and developers across the Group to understand requirements for Responsible AI capabilities and identify enhancement opportunities
• Keep up to date with industry developments and best practise in Generative and Agentic AI, and responsible AI
• Establish strong technical and delivery practices across data science and engineering

We're interested in hearing from people who:

• Are experienced data science or machine learning leaders that combine their strong technical judgement with a people-first approach
• Enjoy solving complex problems, developing others and turning emerging technologies into reliable, practical outcomes
• Communicate clearly, build trusted relationships and can operate effectively across technical, business and risk contexts

Tehcnical skills and qualifications:

• Proven experience leading teams or providing significant technical leadership across machine learning, Generative AI or agentic AI initiatives
• A strong foundation in statistics, probability and machine learning, with the ability to interpret, evaluate and explain model behaviour
• Hands-on experience designing, developing and evaluating production AI or machine learning solutions, including large language models, NLP or conversational AI
• Detailed practical experience in evaluation and managing the risk of Generative and Agentic AI systems
• Advanced Python capability, together with experience using SQL and relevant machine learning or deep learning frameworks
• Practical knowledge of cloud environments such as AWS or Azure, version control, continuous integration and delivery, containerization, monitoring and observability
• Experience applying responsible AI, model governance, risk management and documentation requirements in a regulated or similarly complex environment
• Strong written and verbal communication skills, including the ability to influence senior stakeholders and explain technical decisions to varied audiences
• A tertiary qualification in Data Science, Statistics, Computer Science, Engineering, Mathematics or a related discipline is beneficial
• Experience in software engineering is also beneficial

Working with us

At CommBank, we