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AI Engineer - Internship (Hedge Fund)
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AI Engineer Intern - Long/Short Equities Team
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, summarize, 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.
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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.
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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.
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