Head of AI - Selby Jennings

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
• PyTorch
• TensorFlow
• 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