At a Glance
- Tasks: Develop AI solutions for investment research and enhance decision-making processes.
- Company: WTW, an inclusive employer with a focus on innovation and diversity.
- Benefits: 25 days annual leave, private healthcare, hybrid working, and various perks.
- Other info: Opportunity to collaborate with senior leaders and grow within a dynamic environment.
- Why this job: Make a real impact in investment strategies using cutting-edge AI technology.
- Qualifications: Experience in AI engineering, strong Python and SQL skills, and a relevant degree.
The predicted salary is between 63000 - 77000 £ per year.
This job is with WTW, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community.
At WTW, our Listed Equity team manages over $50bn in equity investment strategies for institutional clients worldwide. As we continue to evolve our investment research capabilities, we are investing in modern data and AI solutions that enhance insight generation, portfolio oversight, and decision-making.
Why Join Us?
- Genuine ownership of the equity team’s AI and data capability — building investment-specific solutions that sit at the intersection of the firm’s broader AI programme and the team’s unique research needs.
- Real investment problems: manager research, portfolio construction, multi-manager oversight.
- Direct impact visibility: your tools will be used by the team in daily investment decisions.
- Gain exposure to senior investment and AI leaders while coordinating with WTW’s wider AI programme.
- Help create a differentiated data and insight capability that becomes more valuable as the team’s knowledge base grows.
The Role
We are seeking an experienced Senior AI Engineer to become the first dedicated AI specialist embedded within our Listed Equity business. This is a unique opportunity to work directly with investment professionals, shaping and delivering innovative AI-driven solutions that create measurable impact across research, analysis, and portfolio management.
Working at the intersection of investments, data, and technology, you will build practical, scalable AI capabilities while leveraging WTW's broader enterprise data and AI ecosystem. As a senior technical specialist within the Listed Equity team, you will:
- Partner with portfolio managers, analysts, and researchers to identify opportunities where AI and data can enhance investment processes and outcomes.
- Assess and map a wide range of equity data sources, including portfolio data, research content, manager communications, and third-party datasets.
- Design and develop the equity-specific data layer, ensuring information is structured, traceable, and aligned with enterprise data standards.
- Build and maintain robust data pipelines and integrations that automate data collection and reduce manual effort.
- Develop, test, and deploy AI-powered solutions and agent-based workflows to support investment research, monitoring, portfolio analysis, and knowledge retrieval.
- Collaborate with WTW's technology, data, and AI teams to align with enterprise architecture, governance, security, and responsible AI standards.
- Document technical solutions and contribute to building AI capability and best practices across the investment team.
Qualifications
What You'll Bring
Essential
- 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.
- Hands-on experience with Large Language Models (LLMs), including Retrieval-Augmented Generation (RAG), prompt engineering, information extraction, evaluation frameworks, and agentic workflows.
- 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.
- Degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline, or equivalent practical experience.
Preferred
- Experience within investment management, asset management, OCIO, or wider financial services environments.
- Familiarity with investment research, portfolio construction, performance analysis, or investment workflows.
- Experience with Microsoft Azure, Microsoft Fabric, Microsoft 365 Copilot, or other enterprise AI platforms.
- Knowledge of financial and market data platforms.
The Application Process
- Apply via WTW careers with your CV and a brief note on a relevant AI or data project you’ve built.
- First-stage online interview with hiring manager and Equity team.
- Technical interview with the Equity team and a member of WTW’s central AI and data team.
- Offer and onboarding.
What we offer
Enjoy a benefits package designed to help you thrive, both professionally and personally. You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge. Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind. Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.
We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community. On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more. Start making the most of your career and wellbeing with a range of benefits tailored for you.
Equal Opportunity Employer
We’re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email.
Senior AI Engineer Investment Research in London employer: WTW
WTW is an exceptional employer that prioritises inclusivity and employee wellbeing, offering a comprehensive benefits package that includes 25 days of annual leave, private healthcare, and a defined contribution pension scheme. The work culture fosters professional growth through hybrid working options and opportunities to engage in meaningful community service, making it an ideal environment for those looking to develop their careers while contributing positively to society.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer Investment Research in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at WTW or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
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Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like WTW that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior AI Engineer Investment Research in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at WTW.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at WTW and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at WTW
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If WTW uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
