At a Glance
- Tasks: Lead the AI function, developing cutting-edge tools for investment management.
- Company: Global multi-strategy investment manager focused on AI innovation.
- Benefits: Highly competitive salary, performance bonuses, and long-term incentives.
- Other info: Unique opportunity to build a team and influence AI strategy from the ground up.
- Why this job: Shape the future of AI in finance and drive real investment impact.
- Qualifications: Proven leadership in AI, machine learning expertise, and strong communication skills.
The predicted salary is between 80000 - 100000 £ per year.
- Head of AI
- Overview
A leading global multi-strategy investment manager is establishing a next-generation AI research and engineering function focused on transforming the investment process through the application of machine learning, large language models, agentic systems and advanced quantitative techniques.
The firm is seeking an exceptional Head of AI to build and lead this function, defining the long-term AI strategy while developing cutting‑edge tools that enhance the capabilities of Portfolio Managers, Quantitative Researchers and investment teams.
This role offers a unique opportunity to operate at the intersection of frontier AI research and systematic investment management, with a clear mandate to generate measurable investment impact and unlock new sources of alpha.
Key Responsibilities
- AI Strategy & Leadership
- Define and execute the firm's AI vision and long‑term roadmap.
- Build and lead a world‑class team of AI Researchers, ML Engineers, Research Scientists and Applied AI Specialists.
- Establish best practices for AI research, experimentation, deployment and governance.
- Act as the senior AI subject matter expert across the organisation.
- Partner directly with senior management, investment leadership and key stakeholders to identify high‑impact opportunities.
- Investment Research & Alpha Generation
- Develop AI‑driven systems capable of generating novel investment insights and alpha signals.
- Apply machine learning, deep learning, reinforcement learning and foundation model techniques to investment research problems.
- Build platforms that enable large‑scale analysis of structured and unstructured financial data.
- Create systems that identify emerging market themes, macroeconomic developments and investment opportunities.
- Partner with investment teams to translate discretionary and systematic hypotheses into scalable AI frameworks.
- Explore the application of agentic AI systems to investment decision‑making workflows.
- Large Language Models & Agentic Systems
- Lead the development of proprietary LLM and agent‑based platforms.
- Deploy AI agents capable of conducting investment research, synthesising information, generating forecasts and supporting portfolio construction.
- Build retrieval‑augmented generation (RAG) systems leveraging internal and external datasets.
- Develop advanced knowledge management and reasoning systems for investment professionals.
- Evaluate frontier AI technologies and identify opportunities for practical deployment within investment workflows.
- Research Platform Development
- Build scalable AI infrastructure supporting experimentation, training, evaluation and deployment.
- Establish rigorous evaluation frameworks for model performance and business impact.
- Create production‑grade systems capable of integrating alternative data, market data, research reports, news and other information sources.
- Implement monitoring, governance and model lifecycle management processes.
- Drive adoption of AI tools across portfolio management and research teams.
- Cross‑Functional Collaboration
- Work closely with Portfolio Managers, Quantitative Researchers, Data Scientists and Technology teams.
- Translate complex investment problems into machine learning solutions.
- Educate stakeholders on emerging AI capabilities and opportunities.
- Foster a culture of innovation and experimentation across the organisation.
- Candidate Requirements
Essential Experience
- Proven experience leading AI, Machine Learning or Research teams.
- Deep expertise in machine learning and modern AI methodologies.
- Experience building and deploying production AI systems at scale.
- Strong understanding of large language models, generative AI and agentic workflows.
- Demonstrated ability to translate research concepts into practical business applications.
- Track record of building high‑performing technical teams.
- Preferred Backgrounds
The ideal candidate may come from
- Frontier AI research labs
- Leading technology companies
- Quantitative hedge funds
- Systematic investment firms
- AI‑first technology startups
- Advanced research institutions
Examples include individuals who have worked on
- Foundation Models
- RLHF and Reinforcement Learning
- Agentic AI
- LLM Infrastructure
- Multi‑Agent Systems
- Search and Reasoning Systems
- AI for Scientific Discovery
- Quantitative Research Platforms
- Technical Expertise
Strong knowledge of several of the following
- Machine Learning
- Deep Learning
- Reinforcement Learning
- Large Language Models
- Agentic Systems
- Natural Language Processing
- Time Series Modelling
- Statistical Learning
- Distributed Training
- Retrieval Systems
- Knowledge Graphs
- MLOps
- AI Infrastructure
Programming expertise in
- Python
- Py Torch
- Tensor Flow
- Distributed Computing Frameworks
- Cloud Infrastructure
- Desired Personal Attributes
- Entrepreneurial mindset.
- Strong leadership capabilities.
- Excellent communication skills.
- Research‑oriented and intellectually curious.
- Ability to operate effectively in fast‑moving, ambiguous environments.
- Commercially minded with a strong focus on investment impact.
- What Makes This Opportunity Unique
- Opportunity to build an AI function from the ground up.
- Significant influence over strategy, team design and technology direction.
- Direct access to investment decision‑makers and senior leadership.
- Ability to work on frontier AI problems with clear real‑world applications.
- Exposure to some of the most challenging prediction and decision‑making problems in global financial markets.
- Opportunity to generate tangible investment outcomes through cutting‑edge AI research and development.
Compensation
Highly competitive compensation package consisting of
- Market‑leading base salary
- Performance‑related bonus Long‑term incentives where applicable
Compensation will be structured to attract exceptional talent from le
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Head of AI - Selby Jennings employer: eFinancialCareers
Quilter plc is an exceptional employer, offering a dynamic work environment in Southampton where innovation and collaboration thrive. With a strong commitment to employee growth, comprehensive benefits including a generous holiday allowance and a non-contributory pension scheme, Quilter fosters a culture of inclusivity and continuous improvement, empowering employees to make meaningful contributions to the financial futures of their clients and communities.
StudySmarter Expert Advice🤫
We think this is how you could land Head of AI - Selby Jennings
✨Get Involved in Finance Communities
Join investment and asset management forums or local finance meetups. Engaging with professionals in these circles can not only help you learn the ropes but also put you in touch with potential employers like eFinancialCareers, who often scout for talent at such events.
✨Utilise Networking Platforms
Connect with professionals already working in asset management on platforms like LinkedIn. A personal message showing your interest in their role or asking for advice can lead to significant connections that might tip the scales in your favour at companies like eFinancialCareers.
✨Show Off Your Financial Skills
Consider contributing to investment blogs or even creating your own content. Sharing your insights and analyses can demonstrate your knowledge and passion for the industry, making you stand out when applying for roles at organisations like eFinancialCareers.
✨Engage with Recruitment Events
Attend finance recruitment fairs and expos. These events are perfect for making a strong impression with recruiters and potentially securing interviews. Many companies, including eFinancialCareers, attend these events to scout for fresh talent, so make sure you stand out with your enthusiasm and knowledge!
We think you need these skills to ace Head of AI - Selby Jennings
Some tips for your application 🫡
Highlight Your Analytical Skills:In asset management, it's all about the numbers! Make sure your CV showcases your analytical skills, particularly any experience with financial modelling or quantitative analysis. Employers like eFinancialCareers want to see how you can dissect data and turn it into actionable insights, so don't hold back on your achievements!
Show Off Your Relevant Qualifications:Having the right qualifications can be a game changer in investment roles. If you've got a degree in finance, economics, or a related field, flaunt it! Also, if you have any certifications like CFA or CAIA, mention those too. It’ll help demonstrate your commitment and expertise in the field to eFinancialCareers.
Tailor Your Cover Letter to Reflect Passion for Investment:Your cover letter is your chance to express your enthusiasm for the investment world. Share why you're drawn to asset management and your understanding of market trends. The hiring team at eFinancialCareers will be keen to see that passion and how you keep up with industry news and developments.
Quantify Your Achievements:Don’t just tell them what you did - show them! When detailing your previous experience, include quantifiable achievements to illustrate your impact. Whether it’s percentage growth on a portfolio or cost savings in a project, these figures will help your application stand out to eFinancialCareers. Numbers speak louder than words!
How to prepare for a job interview at eFinancialCareers
✨Brush Up on Financial Modelling
For a role in investment asset management, being well-versed in financial modelling is crucial. Make sure you can articulate your experience with tools like Excel or any specialised software you've used. Maybe even prepare a couple of examples of financial models you've built or analysed.
✨Know Your Investment Strategies
Expect questions around different investment strategies and how you would apply them in various market scenarios. Get ready to discuss current market trends and how they impact portfolio management. This shows you're not just about the theory but also keeping an eye on real-world applications.
✨Show Your Analytical Skills
Since this is a full-time role, companies like eFinancialCareers want to see your analytical thinking in action. Prepare to solve case studies or tackle some numerical puzzles during the interview. Practicing these types of questions will boost your confidence and show off your skills.
✨Discuss Your Long-Term Career Goals
As you’re applying for a full-time position, the interviewers will be interested in your commitment to the field. Be ready to discuss how this role fits into your long-term career plans in asset management. This shows you're not just looking for any job, but you’re genuinely interested in growing witheFinancialCareers.
