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Commonwealth Bank of Australia

Chapter Lead - Responsible AI, Agentic AI

Commonwealth Bank of Australia is hiring a Chapter Lead - Responsible AI, Agentic AI for a remote role open to applicants in Australia. Level rates it ; you can apply on Commonwealth Bank of Australia.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • This is listed as a remote role.
  • The posting mentions NLP, AI safety and data science among its tools and skills.
  • Commonwealth Bank of Australia has 207 other open roles on Level.
  • Posted in the last few days.

AI in this role

Chapter Lead needed to manage a data science team scaling advanced Responsible AI capabilities for generative and agentic AI.

nlpai-safetydata-sciencegenerative-aiagentic-airesponsible-aileadership

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.


See yourself in our team


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 foster a culture of inclusion and respect, celebrating diversity across cultures, abilities, genders, gender expressions and sexual orientations. If this role excites you but you don’t meet every requirement, we still encourage you to apply as you may be the right fit for this role or another opportunity with us.


We’re committed to making a meaningful difference for Australia’s First Nations peoples and welcome all applicants.

If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career.

We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696.

Advertising End Date: 16/11/2026

How we rate this

Chapter Lead - Responsible AI, Agentic AI at Commonwealth Bank of Australia rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPAI SafetyData ScienceGenerative AIAgentic AIResponsible AILeadership

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. Tell me about a project where data science was part of your work. What did you do?
  4. Tell me about a project where generative ai was part of your work. What did you do?
  5. Tell me about a project where agentic ai was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: NLP, AI Safety, Data Science, Generative AI, and Agentic AI. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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