Junior AI Engineer at AQR Capital Management

London, England, United Kingdom

AQR Capital Management Logo
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Finance, Quantitative FinanceIndustries

Requirements

  • Degree in Computer Science, Engineering, or related technical field, or equivalent industry experience
  • Proficiency in Python and experience with frameworks such as OpenAI Agents SDK, LangChain, LlamaIndex, or Hugging Face Transformers
  • Understanding of RAG and LLM orchestration techniques
  • Experience working with APIs, vector databases (e.g., Qdrant, Pinecone, FAISS, Weaviate), and embedding models
  • Familiarity with cloud platforms (AWS, Azure) and containerized environments
  • Strong grasp of software engineering fundamentals — version control, modular design, testing, and documentation
  • Self-motivated, able to learn quickly, curious, and motivated technologist with strong interest in AI transforming workflows
  • Thrive in collaborative, fast-moving environments, comfortable with hands-on engineering, take initiative in problem-solving, and enjoy scaling new technologies responsibly
  • Desirable Requirements
  • Exposure to agentic AI systems or multi-agent orchestration frameworks
  • Experience building internal tools, SDKs, or developer platforms
  • Familiarity with MLOps, CI/CD for models, and monitoring pipelines
  • Previous experience working in financial markets or investment firms
  • Interest in financial technology or data-rich enterprise environments

Responsibilities

  • Design and implement frameworks for advanced AI capabilities, including LLM-powered applications, RAG systems, agentic process automation, and scalable internal AI tools
  • Collaborate closely with Front Office Technology, Quant Research, Data Technology, Rapid Application Development, and business teams
  • Build, deploy, and maintain scalable AI infrastructure to support quantitative researchers, analysts, and operational users
  • Contribute to real-world financial applications of AI and the firm’s software development lifecycle
  • Help shape tools and standards for responsible, high-performance AI engineering
  • Enhance trading, research, and operational efficiency across the firm through AI integration

Skills

LLMs
RAG
Machine Learning
Generative AI
Agentic Process Automation
AI Infrastructure
Retrieval-Augmented Generation
Quantitative AI

AQR Capital Management

Global investment management firm offering diversified strategies

About AQR Capital Management

AQR Capital Management provides investment management services with a focus on technology, data, and behavioral finance. The firm offers a variety of investment strategies that are based on a consistent set of principles, aiming to achieve long-term and repeatable results. AQR works primarily with institutional investors such as pension funds, insurance companies, and sovereign wealth funds, as well as financial advisors and their clients. Their investment approach combines both qualitative and quantitative methods to carefully design and test investment models. AQR differentiates itself by applying systematic and well-thought-out investment solutions that enhance portfolio construction, risk management, and trading. The company's goal is to deliver value through effective asset management while generating revenue from management and performance fees on the assets they oversee.

Greenwich, ConnecticutHeadquarters
1998Year Founded
VENTURE_UNKNOWNCompany Stage
Quantitative Finance, Financial ServicesIndustries
501-1,000Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
Paid Vacation

Risks

Increased competition from quantitative firms may erode AQR's market share.
The rise of passive strategies like ETFs could impact demand for AQR's services.
Regulatory scrutiny on quantitative trading could increase compliance costs for AQR.

Differentiation

AQR integrates financial theory with practical application for superior investment results.
The firm uses quantitative tools to process fundamental information and manage risk.
AQR's systematic approach aligns with the growing trend of factor investing.

Upsides

AQR can leverage ESG factors in their quantitative models to meet rising demand.
Machine learning advancements enhance AQR's data analysis and predictive modeling capabilities.
AQR can capitalize on personalized investment solutions with their quantitative tools.

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