Oliver Wyman - Senior Lead AI Engineer - Singapore
Marsh & McLennan Companies3 months ago
Singapore, SingaporeStaff+
Responsibilities
- Own the technical journey for AI solutions 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, cost, speed, 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 controls including guardrails, human oversight, access controls, privacy protections, and auditability.
- Collaborate with product owners, business leaders, architects, data specialists, delivery teams, security, privacy, risk, and legal partners.
- Mentor engineers, create reusable patterns and reference implementations, and improve AI engineering practices.
- Explain technical options, risks, and recommendations to technical and non-technical stakeholders, including senior clients and 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, 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 and retrieval, and structured and unstructured information.
- 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.
- A degree in computer science, engineering, or a related discipline, or equivalent professional experience.
- Consulting, professional services, or client-facing technology delivery experience is useful but not essential.
- Regulated-industry or enterprise risk, compliance, and governance experience is useful but not essential.
- Familiarity with AI application frameworks such as Langraph or PydanticAI, model platforms such as Azure Foundry or AWS Bedrock, Kubernetes, and infrastructure as code is useful but not essential.
Benefits
- Hybrid work with flexibility to work remotely and collaborate in the office.
- Colleagues are expected to work from their local office or onsite with clients at least three days per week.
- Office-based teams identify at least one weekly anchor day for in-person collaboration.
- Diverse, inclusive, and flexible work environment.
Tech Stack
Categories
About Marsh & McLennan Companies
Marsh McLennan is a global professional services firm providing risk, insurance and reinsurance brokerage, health, wealth, and management consulting to corporations, governments, and nonprofits. It operates through Marsh, Guy Carpenter, Mercer, and Oliver Wyman, earning fees and commissions for advisory, analytics, and placement services. Founded in 1905 and headquartered in New York, it is publicly traded on the NYSE under the ticker MMC.