Senior AI Engineering Lead — GenAI & Agentic Solutions

Bupa; Melbourne; On-site; AUD 230,000 - 320,000; Full time

Benefits offered by this job

Health benefits

Viva Healthier and Happier program

Career development support

Job summary

Bupa in Melbourne seeks a Senior Technology Manager to lead the AI Hub, driving GenAI and agent-based solutions across the organisation. You will oversee architecture, engineering and the full solution lifecycle, turning AI into scalable enterprise systems while partnering with business teams to deliver measurable value.

You will guide a multidisciplinary AI engineering and delivery team, champion reusable assets, and ensure responsible AI practices, governance, and risk controls are embedded

Qualifications

• 10+ years’ experience delivering complex digital, data, engineering or technology solutions within large enterprise environments.
• 3–5+ years’ experience designing and delivering AI, machine learning or GenAI solutions, with demonstrated experience taking solutions into production.
• Strong technical expertise across GenAI, LLM architecture, RAG, embeddings and vector search, including model selection and evaluation.
• Experience designing Agentic AI solutions, including agent frameworks, orchestration and integration patterns.
• Strong knowledge of AI/ML solution architecture, including APIs, data, identity, security and cloud architecture.
• Experience building enterprise-grade AI platforms and reusable AI capabilities that can scale across complex organisations.
• A strong understanding of AI observability, performance, cost optimisation, production monitoring and Responsible AI controls.
• Demonstrated experience leading multidisciplinary technical teams and technical leaders, while remaining credible and confident in detailed technical discussions.
• Strong stakeholder management and communication skills, with the ability to translate complex AI concepts and technical decisions for executives, business stakeholders and technology teams.
• The technical breadth and confidence to challenge solution designs, identify risks, recommend the right approach and guide senior stakeholders through complex AI decisions.

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 to evaluation, build, testing, deployment, monitoring and optimisation.
• Oversee technical solution design, integrations, APIs, data flows and model selection, ensuring alignment with Bupa’s AI and architecture standards.
• Manage key elements of the AI engineering stack, including LLM platforms, orchestration frameworks, vector databases, retrieval pipelines, security controls and cloud infrastructure.
• Partner with business teams to understand their needs and ensure AI solutions deliver measurable value and improved operational outcomes.
• Help translate Bupa’s AI strategy and roadmaps into practical delivery plans aligned with business priorities.
• Champion reusable AI assets, reference architectures, libraries and shared services to support efficient delivery across Bupa.
• Embed responsible AI practices across solutions, including appropriate safety, privacy, information security, governance, monitoring and model risk controls.
• Build and lead a high-performing AI engineering and solution delivery team, while developing AI capability through coaching, collaboration and communities of practice.

Skills

GenAI

LLM Architecture

Agentic AI

AI Observability

Team Leadership

Stakeholder Mgmt

Job description

Bupa in Melbourne seeks a Senior Technology Manager to lead the AI Hub, driving GenAI and agent-based solutions across the organisation. You will oversee architecture, engineering and the full solution lifecycle, turning AI into scalable enterprise systems while partnering with business teams to deliver measurable value.

You will guide a multidisciplinary AI engineering and delivery team, champion reusable assets, and ensure responsible AI practices, governance, and risk controls are embedded