Senior AI Engineer Investment Research

Overview

In this role, you will embed AI and data capabilities within the Listed Equity team to develop practical, scalable AI-driven solutions for research and portfolio management. You’ll work closely with investment professionals and cross-functional teams to turn data into actionable insights, improving research workflow and decision-making. The position offers direct impact on daily investment processes and exposure to senior AI leaders within a broader AI program. You’ll help build differentiated data and insight capabilities that grow with the team’s knowledge base.

Pay / Benefits

• 25 days annual leave
• private healthcare
• pension with company match
• hybrid working
• volunteer day
• share scheme

Responsibilities

• Identify opportunities where AI and data can enhance investment processes with portfolio managers, analysts, and researchers
• Assess and map equity data sources including portfolio data, research content, manager communications, and third-party datasets
• Design and develop the equity-specific data layer aligned with enterprise data standards
• Build and maintain robust data pipelines and integrations to automate data collection
• Develop, test, and deploy AI-powered solutions and agent-based workflows for investment research, monitoring, and knowledge retrieval
• Collaborate with technology, data, and AI teams to align with governance, security, and responsible AI standards
• Document technical solutions and contribute to building AI capability and best practices across the investment team

Key requirements

• Significant experience in AI engineering, data engineering, software engineering, or a related technical discipline
• Proven track record delivering production-grade solutions with measurable business value
• Strong Python and SQL skills with experience building scalable data pipelines, APIs, and modern data architectures
• Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, information extraction, evaluation frameworks, and agentic workflows
• Solid 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 for engagement with both technical and non-technical stakeholders
• Degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline, or equivalent practical experience

• Clear communication
• Stakeholder engagement
• Collaborative mindset
• Python
• SQL
• Data pipelines and APIs

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