Location
London, London

Hours
Hybrid role requiring 3 days per week from the office

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 role offers the opportunity to work directly with investment professionals, shaping and delivering innovative AI-driven solutions that create measurable impact across research, analysis, and portfolio management.

You will partner with portfolio managers, analysts, and researchers to identify AI and data opportunities, assess and map diverse equity data sources, design and develop the equity-specific data layer aligned with enterprise standards, and build robust data pipelines to automate data collection. You will develop, test, and deploy AI-powered solutions and agent-based workflows supporting investment research, monitoring, portfolio analysis, and knowledge retrieval. Collaboration with WTW’s technology, data, and AI teams is essential to ensure alignment with enterprise architecture, governance, security, and responsible AI standards. Additionally, you will document technical solutions and contribute to building AI capability and best practices across the investment team.

This is a unique chance to work at the intersection of investments, data, and technology, leveraging WTW’s enterprise data and AI ecosystem to deliver practical, scalable AI capabilities with direct impact on daily investment decisions.

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
- 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

About you
Proactive and collaborative professional with a passion for leveraging AI to solve real investment challenges. You thrive working at the intersection of technology and finance, enjoy partnering with diverse teams, and are committed to delivering impactful, scalable solutions while adhering to governance and ethical standards.

Qualifications
- Degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline, or equivalent practical experience
- Experience with Microsoft Azure, Microsoft Fabric, Microsoft 365 Copilot, or other enterprise AI platforms
- Knowledge of financial and market data platforms