2 weeks ago

Senior Lead AI Engineer

Oliver Wyman

Docklands

2 weeks ago

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Oliver Wyman, a Marsh business, is seeking a Senior Lead AI Engineer in Melbourne to lead the design and delivery of secure, reliable AI solutions integrated with enterprise systems. The role requires 10-12 years of software engineering experience, strong architecture skills, and hands-on AI implementation expertise. This is an applied engineering leadership position focused on production AI systems, not research.

AI-enabledHybridFull-timeLeadPythonJava

Senior Lead AI Engineer

Apply

AI-enabledHybridFull-timeLeadPython

Salary

Not specified

Work Location

Docklands, Victoria, Australia, AU

Work Model

Hybrid: at least three days per week in local office or onsite with clients, with remote flexibility

Experience Required

12 years

Employment Type

Full-time

Experience Level

Senior Lead: typically 10-12 years of professional experience

Core Qualifications

Technical (Must-have)

PythonJava.NETTypeScriptNode.jsAWSMicrosoft AzureGoogle CloudSQLKubernetesInfrastructure as CodeCI/CDREST APIsRetrieval-Augmented GenerationMCP

Soft Skills

CommunicationCommercial judgmentMentoringInfluenceCollaboration

Preferred Qualifications

Technical (Nice-to-have)

LangGraphPydanticAIAzure AI FoundryAWS Bedrock

Key Responsibilities

•Lead AI solution delivery from problem framing through production release and continuous improvement
•Design pragmatic architectures connecting AI capabilities with existing applications, APIs, data platforms, identity, security and operational controls
•Build and guide hands-on engineering, establish coding and testing standards, and help teams make trade-offs
•Design and implement agentic applications using agentic harnesses, RAG, MCP, function/tool calling, structured outputs, and multi-agent workflows
•Engineer AI platforms for production including inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability, and cost optimization
•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 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

AI EngineeringSenior LeadEnterprise AISoftware ArchitectureInsuranceBusiness ConsultingMelbourneFull-timeHybridProduction AI

Key Responsibilities

•Lead AI solution delivery from problem framing through production release and continuous improvement

•Design pragmatic architectures connecting AI capabilities with existing applications, APIs, data platforms, identity, security and operational controls

•Build and guide hands-on engineering, establish coding and testing standards, and help teams make trade-offs

•Design and implement agentic applications using agentic harnesses, RAG, MCP, function/tool calling, structured outputs, and multi-agent workflows

•Engineer AI platforms for production including inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability, and cost optimization

•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 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