Senior Technology Manager - AI Hub

About the role

Bupa is looking for a Senior Technology Manager for its AI Hub in Melbourne. You will lead the design, development and delivery of GenAI and agent-based solutions across the organisation, turning advanced AI capabilities into scalable, secure and enterprise-ready solutions. You will oversee architecture, engineering and the full solution lifecycle, work closely with teams across Bupa, and lead a multidisciplinary AI engineering and solution delivery team.

Key responsibilities

• Lead the design, development and operationalisation of GenAI models, intelligent agents, copilots and automation solutions across Bupa.
• Own AI solution delivery end-to-end, from discovery and scoping through evaluation, build, testing, deployment, monitoring and optimisation.
• Oversee technical solution design, integrations, APIs, data flows and model selection, aligned with Bupa's AI and architecture standards.
• Manage the AI engineering stack, including LLM platforms, orchestration frameworks, vector databases, retrieval pipelines, security controls and cloud infrastructure.
• Partner with business teams to ensure AI solutions deliver measurable value and improved operational outcomes.
• Translate Bupa's AI strategy and roadmaps into practical delivery plans.
• Champion reusable AI assets, reference architectures, libraries and shared services.
• Embed responsible AI practices, including safety, privacy, information security, governance, monitoring and model risk controls.
• Build and lead a high-performing AI engineering and solution delivery team, developing AI capability through coaching, collaboration and communities of practice.

Required profile

• 10+ years' experience delivering complex digital, data, engineering or technology solutions in large enterprise environments.
• 3-5+ years' experience designing and delivering AI, machine learning or GenAI solutions, with proven experience taking them into production.
• Demonstrated experience leading multidisciplinary technical teams and technical leaders.
• Strong stakeholder management and communication skills, able to explain complex AI concepts to executives, business stakeholders and technology teams.

Required skills

• GenAI, LLM architecture, RAG, embeddings and vector search, including model selection and evaluation.
• Agentic AI solutions, including agent frameworks, orchestration and integration patterns.
• AI/ML solution architecture covering APIs, data, identity, security and cloud.
• Building enterprise-grade AI platforms and reusable AI capabilities.
• AI observability, performance, cost optimisation, production monitoring and responsible AI controls.