Location
London (Hybrid role requiring 3 days per week in the office)

Hours
Full Time

Salary
Negotiable

About the Role
At WTW, our Listed Equity team manages over $50bn in equity investment strategies for institutional clients worldwide. We are investing in modern data and AI solutions to enhance insight generation, portfolio oversight, and decision-making. As a Senior AI Engineer embedded within our Listed Equity business, you will have genuine ownership of the equity team’s AI and data capabilities, building investment-specific solutions that integrate with the firm’s broader AI programme and meet the team’s unique research needs.

This unique role involves working directly with investment professionals to shape and deliver innovative AI-driven solutions that create measurable impact across research, analysis, and portfolio management. You will work at the intersection of investments, data, and technology, building practical, scalable AI capabilities while leveraging WTW's enterprise data and AI ecosystem.

Key responsibilities include partnering with portfolio managers, analysts, and researchers to identify AI opportunities, assessing and mapping equity data sources, designing and developing an equity-specific data layer aligned with enterprise standards, building and maintaining data pipelines, developing AI-powered solutions and agent-based workflows, collaborating with technology and AI teams to ensure governance and security compliance, and documenting technical solutions to build AI capability and best practices across the investment team.

Your work will have direct impact visibility as your tools will be used daily in investment decisions, and you will gain exposure to senior investment and AI leaders while coordinating with WTW’s wider AI programme.

Experience
- Experience within investment management, asset management, OCIO, or wider financial services environments.
- Familiarity with investment research, portfolio construction, performance analysis, or investment workflows.
- Hands-on experience with Large Language Models (LLMs), including Retrieval-Augmented Generation (RAG), prompt engineering, information extraction, evaluation frameworks, and agentic workflows.
- Significant experience in AI engineering, data engineering, software engineering, or a related technical discipline.
- Demonstrated success delivering production-grade solutions that drive measurable business value.
- Strong Python and SQL skills, with experience developing scalable data pipelines, APIs, and modern data architectures.
- Strong understanding of data governance, security, privacy, and responsible AI principles.
- Experience designing and deploying scalable cloud-based or enterprise applications.
- Experience with Microsoft Azure, Microsoft Fabric, Microsoft 365 Copilot, or other enterprise AI platforms.
- Knowledge of financial and market data platforms.

About you
- Ability to translate complex business problems into practical technical solutions.
- Strong communication skills with the ability to engage effectively with both technical and non-technical stakeholders.

Qualifications
- Degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline, or equivalent practical experience.