AI Engineer - Internship (Hedge Fund)

We are seeking an exceptional AI Engineer Intern to join a Long/Short Equities team at a leading global hedge fund. This is a 6–12 month internship for a technically strong candidate with deep interest in AI, large language models and software engineering, who can help build practical AI tools for use by investment professionals. This is a highly hands-on role. The successful candidate will be expected to work closely with Portfolio Managers and Analysts to understand their workflows, identify opportunities for AI-enabled tooling, and build applications that improve research, idea generation, information retrieval, portfolio monitoring and decision-making. We are looking for someone who can take ownership across the technology stack — from data ingestion and model orchestration through to backend services and user-facing front-end applications. The role will suit a candidate with strong LLM experience, solid software engineering foundations and the ability to turn ambiguous investment problems into robust, usable tools. Key Responsibilities Build AI tools and applications for the Long/Short Equities team, from initial concept through to deployment and iteration. Own the full technology stack for team-specific AI tooling, including front-end interfaces, backend services, data pipelines, model integration and application logic. Develop user-friendly tools that help Portfolio Managers and Analysts search, summarise, interrogate and extract insights from company filings, earnings transcripts, broker research, news, internal notes and other relevant datasets. Design and implement LLM-powered workflows, including retrieval-augmented generation, document search, summarisation, classification, entity extraction, question answering and research automation. Integrate large language models and related AI services into practical applications using appropriate APIs, orchestration frameworks and evaluation techniques. Build robust data pipelines to collect, clean, structure and maintain structured and unstructured data sources. Work directly with investment professionals to translate research and investment needs into technical requirements and product features. Develop and maintain backend services, APIs and databases to support AI-driven applications. Build intuitive front-end interfaces that allow non-technical users to interact effectively with AI tools. Evaluate model outputs for accuracy, relevance, consistency and usefulness in an investment context. Apply strong software engineering practices, including clean code, version control, documentation, testing and maintainability. Iterate quickly based on user feedback, ensuring tools are reliable, practical and adopted by the team. Stay current with developments in AI, LLMs, software engineering and investment technology. Candidate Profile We are looking for a high-calibre candidate with a completed or near-completed Master’s degree in a relevant technical, scientific or quantitative discipline, such as Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, Statistics, Physics or a related field. The successful candidate should have: Strong hands-on experience working with large language models , including practical use of LLM APIs and AI application development. Solid software engineering experience , with the ability to build reliable, maintainable and user-focused tools. Strong programming skills, particularly in Python . Experience building applications across the full stack , including backend services and front-end user interfaces. Familiarity with APIs, databases, data pipelines and working with structured and unstructured datasets. Experience with LLM workflows such as retrieval-augmented generation, embeddings, semantic search, prompt engineering, model evaluation and context management . Ability to take ownership of technical projects end to end, from problem definition and architecture through to implementation and user feedback. Interest in equities, financial markets and investment research. Strong analytical and problem-solving skills, particularly in ambiguous or fast-moving environments. Excellent communication skills, with the ability to work closely with non-technical investment professionals. High attention to detail, intellectual curiosity and a practical, delivery-focused mindset. Desirable Skills Experience with frameworks and tools such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face or similar. Experience with React, TypeScript, JavaScript, FastAPI, Flask, Django or similar front-end and backend technologies. Knowledge of vector databases, embeddings, semantic search and document retrieval systems. Experience with SQL and database design. Familiarity with Git, Docker, CI/CD, testing frameworks and cloud platforms. Experience building internal tools, dashboards, workflow automation or productivity applications. Exposure to financial datasets, company filings, earnings calls, broker research, market data or investment research workflows. Prior internship, project or work experience in finance, fintech, AI, data science or software engineering. What We Offer Direct exposure to a high-performing Long/Short Equities investment team. The opportunity to build AI tools that are used in a real investment environment. Significant ownership of technical projects and the team’s AI tooling stack. Hands-on experience applying LLMs and software engineering to live investment problems. Close collaboration with experienced Portfolio Managers and Analysts. A steep learning curve across AI, equities, software engineering and investment decision-making. A high-calibre, intellectually rigorous and entrepreneurial working environment.