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. You will work alongside quant researchers and COO management to build backend services, data pipelines, and internal APIs that improve productivity, deepen AI adoption, and make better use of the data the business already has access to.
AI integration is a core part of this role, not an afterthought. We are actively building out how LLMs, agentic workflows, and AI-powered tooling fit into the investment process, and this hire is expected to drive a meaningful part of that. You should come in with both hands-on experience and genuine conviction about where these technologies are heading.
The role sits close to the investment process. We are looking for someone proactive and delivery-focused: someone who identifies what needs to be built, takes ownership, and gets it done without waiting to be directed. The expectation is high-quality output, pragmatic solutions that work in the hands of investment professionals and create immediate value.
What you'll do- 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, with the awareness that this is a rapidly evolving landscape requiring continuous reassessment of what best looks like
- Build and maintain a shared AI plugin and skills library that can be leveraged by all Fundamental Equity investment professionals, ensuring capabilities are well-documented, reusable, and model-agnostic
- 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
What you'll bringWhat you need:
- 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. You have built things with these, not just read about them
- 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 IaC tooling
- 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
- Actively engaged 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. The team culture is open, engaged, and friendly, and we are looking for someone who genuinely thrives in that environment
- Product-minded: you think about who is using the tool and what problem it solves, not just whether the code runs
- Comfortable in a business-facing team where pace matters and requirements evolve. This is not a research lab environment
- Self-starter who takes ownership end-to-end, from scoping and delivery through to maintenance and iteration
- Intellectually curious about financial markets and the investment process
We'd love if you had:
- 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
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.
