Full-Time

Senior Lead AI Engineer

Melbourne

Updated on 8/22/2026

Marsh & McLennan

Marsh & McLennan

Risk, insurance and business consulting

No salary listed

Melbourne VIC, Australia

Hybrid

At least three days per week in the local office or onsite with clients.

Bachelor's

Category
AI & Machine Learning (1)
Required Skills
Kubernetes
Microsoft Azure
Python
Distributed Systems
Node.js
SQL
Machine Learning
Java
Infrastructure as Code (IaC)
RAG
TypeScript
Version Control
.NET
AWS
Observability
DevOps
Google Cloud Platform
Requirements
  • Typically 10-12 years of professional experience in software engineering, solution architecture, platform engineering or related enterprise technology roles.
  • A strong record of designing and delivering production enterprise applications, integrations or digital platforms in complex, regulated or security-conscious environments.
  • Recent hands-on experience implementing AI-enabled solutions, such as agentic applications, retrieval-augmented generation, intelligent workflow automation or machine-learning services.
  • Strong software engineering fundamentals, including API design, distributed systems, automated testing, version control, continuous integration and continuous delivery, observability and secure development practices.
  • Proficiency in Python and practical experience with at least one enterprise application stack such as Java, .NET or TypeScript/Node.js.
  • Experience delivering on at least one major cloud platform.
  • Working knowledge of enterprise data integration, SQL, search/retrieval and the handling of structured and unstructured information.
  • Practical understanding of model and application evaluation, prompt and context design, privacy, security, responsible AI controls and production monitoring.
  • Experience leading technical work across multidisciplinary teams, mentoring engineers and influencing architecture or engineering standards without relying solely on formal authority.
  • Clear communication, commercial judgment and the ability to translate ambiguous business needs into a feasible technical approach and delivery plan.
  • Appropriate approval to work in Australia.
  • Successful completion of a Criminal and Bankruptcy check prior to commencing employment.
Responsibilities
  • Own the technical journey from problem framing and feasibility assessment through architecture, implementation, production release and continuous improvement.
  • Create pragmatic architectures that connect AI capabilities with existing applications, APIs, data platforms, identity, security and operational controls.
  • Develop or review critical components, establish coding and testing standards, and help teams make sound trade-offs across quality, cost, speed and maintainability.
  • Design and implement agentic applications using agentic harnesses, retrieval-augmented generation, MCP, function/tool calling, structured outputs and multi-agent workflows where appropriate.
  • Design inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability and cost optimization for enterprise-scale AI applications.
  • Define evaluation criteria, test sets, observability and feedback loops for accuracy, reliability, safety, latency, cost and business impact.
  • Work with security, privacy, risk and legal partners to implement guardrails, human oversight, access controls and auditability.
  • Collaborate with product owners, business leaders, architects, data specialists and delivery teams to turn priorities into achievable roadmaps.
  • Mentor engineers, contribute reusable patterns and reference implementations, and help teams adopt effective AI engineering practices.
  • Explain solution options, risks and recommendations clearly to technical and non-technical stakeholders, including senior client or business leaders.
Desired Qualifications
  • Consulting, professional services or client-facing technology delivery experience.
  • Experience in a regulated industry or with enterprise risk, compliance and governance processes.
  • Familiarity with AI application frameworks such as Langraph or PydanticAI, or model platforms such as Azure Foundry or AWS Bedrock.
  • Experience operating containerized workloads or collaborating with platform teams using Kubernetes and infrastructure as code.
  • A degree in computer science, engineering or a related discipline, or equivalent professional experience.

Marsh, formerly Marsh McLennan, is a global professional services firm focused on risk, insurance, reinsurance, talent and business strategy. Its operating businesses help organizations arrange coverage, model and transfer risk, design workforce programs and address complex management questions. Clients range from growing companies to governments and multinational enterprises. The group combines advisory expertise with insurance-market access and data, making it broader than an insurance broker alone while remaining primarily a business-to-business services organization.

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