Head of AI Centre of Excellence (Data Science, Agentic & Gen AI)
Lead the AI Centre of Excellence for a global financial organisation, shaping strategy and driving Agentic and Generative AI initiatives across business banking. Manage a team of 12-14 data scientists and oversee productionisation of advanced AI systems with technical and commercial leadership. Provide strategic guidance, risk management, and cross-functional collaboration within a matrix team structure.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Head of AI Centre of Excellence (Data Science, Agentic & Gen AI)
We're conducting a GLOBAL SEARCH for an industry-leading organisation who are at the frontier of the AI revolution, who are looking to attract the best AI talent on the planet.
This role will be based in office in SYDNEY but a full relocation and immigration support will be offered!
The Role:
Reporting directly to the GM of a particular business unit, you will be responsible for owning and shaping the AI Centre of Excellence for one of the worlds largest organisations in their industry.
This role requires deep technical AI leadership capability, alongside great people management experience, responsible for a team of 12-14 Data Scientists.
You will operate within a matrix team structure, working closely with AI product and engineering teams.
The Ideal Profile:
Looking to advance your Machine Learning & AI career with relocation support? Explore Machine Learning & AI Jobs with Relocation Packages that include comprehensive packages to help you move and settle in your new role.
- A strong foundation in Data Science and Artificial Intelligence, with breadth across the discipline (This is NOT an Engineering or Product mandate)
- Demonstrable experience spanning both traditional ML/AI and modern Generative and Agentic AI paradigms.
- A proven track record of productionising Agentic AI systems, ideally including the design and deployment of multi-agent architectures.
- Technical depth to operate at the detail level, covering areas such as orchestration, guardrails, architectural trade-offs, and failure mode analysis.
- The commercial acuity to connect system design and technical decisions to business value, risk management, and product strategy.
- Experience operating within large, complex enterprise environments.
What you'll do:
- Engage stakeholders, leaders and partners to identify, scope and prioritise high impact AI initiatives.
- Manage the risk profile for the team and contribute to raising risk standards including through responsible AI and enhanced model management practices.
- Actively partner to shape the requirements for AI Platform and infrastructure needed to scale AI safely, leveraging new capabilities being made available at the Group level.
Discover our full range of relocation jobs with comprehensive support packages to help you relocate and settle in your new location.
Key Responsibilities:
- Develop and communicate a strategic vision for AI initiatives, aligning them with organisational goals and driving the overall AI strategy.
- Lead the development of innovative Agentic AI and Gen AI solutions to complex organizational problems, leveraging advanced technical knowledge and specialist expertise.
- Build, lead and coach a diverse, talented team of data scientists providing thought leadership and technical guidance to progress the strategy, road map and delivery of prioritized AI and modelling initiatives and capabilities.
- Conduct and oversee advanced research to apply new methods and technologies to solve complex problems, ensuring the organisation stays ahead of industry trends and accelerate agile innovation.
- Provide strategic and hands-on technical leadership in orchestrating, building and deploying Agentic AI solutions, and ensuring projects are executed with technical excellence and innovation.
- Work closely with other AI and Data Science bar raisers to build a culture of performance and contribute to craft across the entire AI and Data Science Practice.
- Actively partner with internal AI and data science teams and external strategic partners to share knowledge, best practices and bring the best of AI led impact to Business Bank.
- Gen AI and Agentic AI Initiatives: Drive the expansion and adoption of Generative AI and Agentic AI solutions within business banking. Optimize product offerings, enhance customer experiences, and simplify internal processes through the design, development, and integration of these AI technologies.
- Enable AI team: Upskill AI and data science practitioners and enhance capabilities in key techniques such as prompt design, RAG, fine-tuning, agentic AI frameworks. Ensure expertise in tools and establish best practices for monitoring, testing, and validating Gen AI solutions.
- Develop Transferrable and Re-usable Frameworks: Collaborate with technology and engineering teams to design and build standardized Gen AI assets applicable across the team
Interested in relocating to Australia? Check out our comprehensive Relocation Jobs in Australia page with detailed relocation packages and benefits.
Desired Skills and Experience
Leadership and Coordination:
- Proven experience in leading high-performing multidisciplinary teams with skills spread across Gen AI, Agentic, predictive ML , ML Ops and Data Science.
- Demonstrated capability in driving reusable Gen AI outcomes that can be leveraged across the group.
- Proficiency in risk management strategies to identify, mitigate, and manage AI-related risks.
Technical Skills and Tools:
- Generative AI Hands-On Delivery Experience: Demonstrated hands-on experience as a data scientist, with recent expertise in building and productizing Agentic AI and Generative AI solutions in a business context.
- Expertise includes: Hands-on coding, prompt engineering, RAG, guardrail design, orchestration design, and familiarity with frameworks like Semantic Kernel and LangGraph.
- Machine Learning: Expertise in designing and constructing machine learning models, including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of predictive models.
- Tooling: Hands-on experience in building enterprise level AI agents using Gen AI, traditional ML and data science tools such as LLM, RAG, Spark, Python, R, TensorFlow, PyTorch, SQL, and key AWS integration packages.
- AI Platforms: Demonstrated experience in developing, deploying, and monitoring Agentic AI, Gen AI and ML models on AWS infrastructure, including Bedrock, Sage Maker, Knowledge Base, and OpenSearch.
Similar Jobs
Explore other opportunities that match your interests
Machine Learning Engineer, Applied AI
SimplePractice
Staff Machine Learning Engineer - ML Training Infrastructure
General Motors
Senior Research Engineer - RL Velocity Team