17 days ago
Melbourne, AustraliaStaff+
Responsibilities
- Own AI solution delivery from problem framing and feasibility assessment through architecture, implementation, production release, and continuous improvement.
- Design enterprise architectures connecting AI capabilities with applications, APIs, data platforms, identity, security, and operational controls.
- Develop or review critical software components and establish coding, testing, quality, and maintainability standards.
- Build production agentic applications using agentic harnesses, retrieval-augmented generation, MCP, function and tool calling, structured outputs, and multi-agent workflows.
- Design production AI platform capabilities 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.
- Implement responsible AI guardrails, human oversight, access controls, privacy protections, and auditability with relevant partners.
- Collaborate with product owners, business leaders, architects, data specialists, and delivery teams on achievable roadmaps.
- Mentor engineers, develop reusable patterns and reference implementations, and improve AI engineering practices.
- Communicate technical options, risks, and recommendations to technical and non-technical stakeholders, including senior clients or business leaders.
Requirements
- Typically 10-12 years of professional experience in software engineering, solution architecture, platform engineering, or related enterprise technology roles.
- 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, CI/CD, 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, with depth in one environment preferred over superficial coverage of AWS, Microsoft Azure, and Google Cloud.
- Working knowledge of enterprise data integration, SQL, search/retrieval, and 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 ability to translate ambiguous business needs into feasible technical approaches and delivery plans.
- Consulting, professional services, or client-facing technology delivery experience is useful but not essential.
- Experience in regulated industries or enterprise risk, compliance, and governance processes is useful but not essential.
- Familiarity with AI application frameworks such as Langraph or PydanticAI, or model platforms such as Azure Foundry or AWS Bedrock, is useful but not essential.
- Experience operating containerized workloads or collaborating with platform teams using Kubernetes and infrastructure as code is useful but not essential.
- A degree in computer science, engineering, or a related discipline, or equivalent professional experience.
Benefits
- Hybrid work with flexibility to work remotely and collaborate in the office, with colleagues expected to work in their local office or onsite with clients at least three days per week.
- Office-based teams identify at least one weekly anchor day for the full team to work together in person.
- Flexible and inclusive work environment with collaboration, connection, and professional development benefits.
- Employment is in Melbourne, Australia, and applicants must have appropriate approval to work in Australia.
- Successful applicants must complete a Criminal & Bankruptcy check before commencing employment.
Tech Stack
Categories
About Marsh
Marsh is a global insurance broker and risk advisor that helps businesses, public entities, and individuals assess, transfer, and manage risk through insurance placement, captives, and advisory services. It sells brokerage, risk consulting, and claims management across industries, including cyber and property, and operates in more than 130 countries. Marsh is a business of Marsh McLennan and is headquartered in New York.