Software Engineer - Fundamental Equities

About the role

We are looking for a Software Engineer to join the Fundamental Equity COO team, embedded directly within the business rather than in a central technology function. The role sits close to the investment process and requires both hands-on experience and genuine conviction about the direction of AI technologies.

Responsibilities

• Write clean, well-structured, maintainable code and contribute to good engineering practices within the team, including CI/CD pipelines and version control, with an active contribution to firmwide best practices so that deliverables can be broadly leveraged across the business
• Build, deploy, and maintain internal APIs (FastAPI) and backend services that surface portfolio analytics, market data, and quantitative outputs to investment professionals, hosted within the team’s AWS environment
• Own and extend scheduled data pipelines and orchestration workflows (Prefect) running in containerized environments (Docker, Kubernetes), ensuring reliability and observability across the platform
• Contribute to the AI integration layer in close coordination with central Technology teams: strategically implementing and operating AI capabilities tailored to the specific needs of the Fundamental Equity business, spanning LLM APIs, MCP servers, and agentic workflows across a multi-model architecture
• Develop and own structured databases (PostgreSQL) underpinning research, portfolio, and operational workflows, with a view to making that data increasingly accessible and actionable through AI

Requirements

• 2–5 years of experience in a relevant role: quantitative development, dev strats, analytics engineering, or quantitative analysis at a bank, hedge fund, asset manager, or financial data provider
• Strong Python proficiency with an emphasis on well-structured, object-oriented codebases; solid SQL and database design skills, particularly PostgreSQL
• Experience building and deploying backend services and APIs (FastAPI or equivalent) in a production environment
• Hands-on experience with AI/LLM integration across multiple model providers: API usage, prompt engineering, tool use, and retrieval-augmented workflows
• Practical familiarity with MCP servers, agentic frameworks, or multi-model orchestration architectures (custom implementations or equivalent)
• Experience with AI-assisted development tools (e.g. Claude Code, Cursor, or similar) as part of a day-to-day engineering workflow
• Comfortable working within AWS: EC2, containerized workloads, and infrastructure managed via Terraform or similar
• Experience with Docker, Kubernetes, and workflow orchestration frameworks (Prefect, Airflow, or equivalent)
• Sound software engineering fundamentals: version control, structured codebases, CI/CD pipelines, documentation, testing
• Active engagement with the AI development landscape: you follow what is changing, test new tools and frameworks hands-on to form your own views, and translate those views into practical decisions about what to build and how
• Collaborative by nature: you share ideas openly, contribute to collective knowledge, and are comfortable working across technical and non-technical audiences, from quant researchers and central Tech teams to investment professionals
• Experience building dashboards or lightweight frontend interfaces (e.g. Streamlit, React) for internal users
• Exposure to alternative data ingestion or vendor API integrations
• Prior experience in a hedge fund or multi-manager platform

Qualifications

• Intellectual curiosity about financial markets and the investment process
• Self-starter who takes ownership end-to-end, from scoping and delivery through to maintenance and iteration

Skills

• Python
• SQL
• PostgreSQL
• FastAPI
• Docker
• Kubernetes
• Prefect
• AWS
• CI/CD pipelines
• Version control
• Structured codebases
• AI/LLM integration
• MCP servers
• Agentic frameworks
• Multi-model orchestration architectures
• AI-assisted development tools
• Alternative data ingestion
• Vendor API integrations

Benefits

The base pay for this role is expected to be between $150k and $175k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.