Agentic AI Engineer

About the role

We are a leading global hedge fund that sits at the intersection of high-performance computing, quantitative research, and innovative financial strategies. Our organization prides itself on a culture of intellectual curiosity, rigour, and the pursuit of alpha through technological excellence. By joining our team, you will be part of an elite group of engineers and researchers dedicated to pushing the boundaries of what is possible in the financial markets.

Responsibilities

• Architect Agentic Workflows: Design and deploy robust multi-agent systems using frameworks such as LangGraph, AutoGen, or CrewAI to automate complex analytical and operational tasks.
• Cognitive Architecture Development: Implement advanced reasoning patterns including Chain-of-Thought, ReAct, and self-reflection loops to ensure high-fidelity decision-making by AI agents.
• Tool Integration: Build and maintain secure interfaces between AI agents and internal data APIs, financial modelling tools, and execution environments.
• Performance Optimisation: Monitor, analyse, and optimise agent behaviour for latency, reliability, and cost-effectiveness, ensuring systems can handle high-frequency financial data.
• Cross-functional Collaboration: Work closely with Quantitative Researchers and Portfolio Managers to identify opportunities where agentic automation can accelerate the research cycle or improve operational efficiency.
• Research & Innovation: Stay at the forefront of the rapidly evolving AI landscape, evaluating new papers and open-source models to integrate state-of-the-art capabilities into our ecosystem.

Requirements

• A strong background in Software Engineering with expert-level proficiency in Python.
• Proven experience building applications with Large Language Models (LLMs) and a deep understanding of agentic design patterns and orchestration frameworks.
• Proficiency in working with vector databases (e.g., Pinecone, Milvus, Weaviate) and implementing sophisticated Retrieval-Augmented Generation (RAG) pipelines.
• Exceptional problem-solving skills and the ability to analyse complex system behaviours in a high-stakes environment.

Qualifications

• A Master’s degree or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.
• Experience within a hedge fund, investment bank, or fintech environment is highly desirable but not essential for a candidate with world-class technical skills.

Skills

• Expert-level proficiency in Python.
• Experience with Large Language Models (LLMs).
• Understanding of agentic design patterns and orchestration frameworks.
• Proficiency in vector databases and RAG pipelines.

Benefits

• Competitive salary and performance-linked bonuses that reflect the high-value nature of this role.

Pay

• Competitive compensation package.

Schedule

• Full-time position.