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Marsh & McLennan

Brokers insurance and runs risk and HR consulting

Senior Lead AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSydney NSW, AustraliaNo salary listed

About the Job

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; depth in one environment is more important than superficial coverage of AWS, Microsoft Azure, and Google Cloud.
  • Working knowledge of enterprise data integration, SQL, search and retrieval, and handling structured and unstructured information; specialist data-platform engineering is not required.
  • 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.

Responsibilities

  • Lead the technical journey for AI solution delivery from problem framing and feasibility assessment through architecture, implementation, production release, and continuous improvement.
  • Create pragmatic enterprise architectures connecting 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 production agentic applications using agentic harnesses, retrieval-augmented generation, MCP, function and 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 appropriate 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 one or more AI application frameworks, such as LangGraph 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.

About the Company

Marsh & McLennan

Brokers insurance and runs risk and HR consulting

Marsh & McLennan Companies, which operates under the Marsh brand, is an insurance broker and consulting group serving businesses, governments and institutions worldwide. Its Marsh Risk unit arranges property, casualty, cyber and employee-benefit coverage, while Guy Carpenter places reinsurance for insurers. Mercer advises employers on pay, benefits, retirement and investments, and Oliver Wyman, Lippincott and NERA handle strategy, brand and economic consulting. Brokers earn commissions and fees from placing coverage, and consultants bill client fees or charge fees based on assets or plan members. The company traces its roots to 1871 and is headquartered in New York City.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
New York, NY
Founded
1871

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