Oliver Wyman - AI Engineer, Singapore

Company:

Oliver Wyman Description:

Who We Are

At Oliver Wyman, a Marsh (NYSE: MRSH) business, we bring deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments.

As a business of Marsh, we work alongside the world’s leading experts across risk, reinsurance and capital, people and investments, and management consulting. Together with Marsh Risk, Guy Carpenter, and Mercer, we help organizations build resilience and competitive advantages from every angle. With annual revenue of $27 billion and more than 95,000 colleagues in 130 countries, Marsh helps build the confidence to thrive through the power of perspective.

For more information, visit oliverwyman.com .

Job Overview

We are seeking an AI Engineer to design, build, deploy, and scale enterprise AI, machine learning, and Generative AI solutions that create measurable business value.

This role sits at the intersection of AI engineering, data engineering, cloud architecture, and solution delivery. The successful candidate will help develop production-ready AI systems, including LLM-powered applications, retrieval-augmented generation (RAG), agentic workflows, and data-driven architectures across cloud and hybrid environments.

In this role, you will partner with business and technology stakeholders to identify high-value opportunities, shape solution designs, and deliver AI-enabled products that improve productivity, support better decision-making, enhance operational efficiency, and strengthen customer outcomes.

You will also contribute to the organization’s broader AI capability by evaluating emerging technologies, sharing best practices, and helping advance responsible AI adoption. This is an opportunity to work collaboratively across multidisciplinary teams and help shape AI engineering standards, frameworks, and delivery practices in a fast-evolving environment.

What You Will Do

AI solution design and delivery

• Design, develop, and deploy enterprise AI, machine learning, and Generative AI solutions that address complex business challenges and deliver measurable value.
• Translate business needs into scalable technical architectures, solution designs, and implementation plans.
• Build production-ready AI applications using large language models (LLMs), RAG, agentic workflows, and advanced machine learning techniques.
• Support the full solution lifecycle, from ideation and prototyping through deployment, monitoring, and continuous enhancement.
• Develop reusable assets, frameworks, accelerators, and delivery practices that improve efficiency and consistency across initiatives.

Generative AI and agentic systems

• Design and implement LLM-powered applications using leading AI platforms and models, such as OpenAI, Anthropic Claude, Llama, and other foundation models.
• Develop agentic workflows and multi-agent systems using orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or similar tools.
• Apply prompt engineering, tool/function calling, memory management, retrieval techniques, and coordination patterns to improve solution performance.
• Evaluate and optimize model and application behavior through experimentation, benchmarking, fine-tuning, and prompt refinement.
• Stay informed about developments in Generative AI and agentic technologies and assess their relevance to business needs.

Data engineering and AI platform enablement

• Design, develop, and maintain scalable data pipelines that support AI, machine learning, and analytics workloads.
• Integrate structured and unstructured data from internal systems and external sources.
• Build and optimize retrieval architectures using relational databases, NoSQL systems, vector databases, and knowledge repositories.
• Work closely with data engineering and architecture teams to support dat