Hybrid Lead AI Engineer

at AustralianSuper

• Job title: Lead AI Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Docker, Google Cloud Platform, JavaScript, Kubernetes, Python
• Location requirements: Hybrid, Melbourne, Australia

About the role

• Lead AI Engineer at AustralianSuper designing and delivering production‑grade GenAI solutions. Guiding a high-impact team while ensuring robust, scalable, and secure implementations.

Responsibilities

• Lead the technical design and delivery of GenAI solutions from LLM and RAG foundations through to agentic AI systems.
• Design, build, and deliver production‑grade AI solutions that move beyond experimentation and into real‑world impact.
• Provide technical leadership for a small, high‑impact team of AI engineers while remaining deeply hands‑on in solution design, development, and delivery.
• Ensure solutions are robust, scalable, secure, and responsibly designed, aligned with enterprise standards and regulatory expectations.

Requirements

• Strong hands‑on experience building GenAI solutions, including LLM integration, prompt engineering, RAG patterns, and evaluation approaches in production environments.
• Demonstrated capability in prompt design and optimisation, including structuring system and user prompts, managing context, reducing hallucinations, and improving output consistency and reliability.
• Experience designing and delivering agentic AI systems, such as tool‑using agents, workflow orchestration, multi‑step reasoning, and human‑in‑the‑loop patterns.
• Hands‑on expertise with cloud platforms (AWS, Azure, or GCP), including deploying and operating AI solutions in cloud‑based environments.
• Experience with containerisation and orchestration, including Docker and Kubernetes, to support scalable, reliable AI services.
• Advanced programming skills in Python and/or JavaScript, used to build, integrate, and operate GenAI and agentic systems across APIs, services, and workflows.
• Demonstrated experience with MLOps / GenAI operations practices, including lifecycle management, deployment pipelines, monitoring, and operational support.
• Experience embedding and operationalising Responsible AI and ethical AI principles, applying best‑practice patterns across GenAI and agentic use cases in enterprise or regulated environments.
• Strong software engineering and system design skills, with the ability to balance experimentation with production readiness, performance, cost, and maintainability.
• Experience leading technical delivery, providing clear technical direction, reviewing designs and code, and supporting the development of other engineers while remaining hands‑on.
• Strong communication and stakeholder engagement skills, able to translate complex technical concepts for both technical and non‑technical audiences.
• An innovative, curious, and growth‑oriented mindset, with a desire to continuously learn and apply emerging AI capabilities in practical ways.
• Relevant certifications and experience in financial services or large global organisations are highly regarded.

Benefits

• Flexible, hybrid working environment
• Ongoing learning, coaching and training
• Career opportunities across global organisation
• Generous leave entitlements