Software Engineer - Fundamental Equities

Schonfeld; New York (NY); On-site; USD 150,000 - 175,000; Full time

Benefits offered by this job

Learning and educational offerings

Performance bonus

Competitive benefits package

Job summary

Schonfeld, a global multi-manager hedge fund, is hiring a Software Engineer in New York to join the Fundamental Equity COO team. The role focuses on integrating AI into investment processes, building backend services and data pipelines.

Candidates should have 2–5 years of experience, strong Python and SQL skills, and familiarity with tools like FastAPI and PostgreSQL. The team values collaboration and product-focused thinking to deliver high-quality solutions.

Qualifications

• 2–5 years of experience in quantitative development or analytics engineering.
• Experience with AWS and containerized workloads.
• Familiarity with CI/CD pipelines and version control.

Responsibilities

• Develop backend services and internal APIs for investment professionals.
• Implement AI capabilities tailored to business needs.
• Maintain data pipelines ensuring reliability and observability.

Skills

Python proficiency

SQL and database design

AI/LLM integration

Collaboration

Product-minded thinking

Tools

FastAPI

PostgreSQL

Docker

Kubernetes

Job description

Software Engineer - Fundamental Equities

New York, New York, United States

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 bring

What 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
• 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

Who we are

Schonfeld is a global multi‑manager hedge fund that strives to deliver industry‑leading risk‑adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.

Our Culture

At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork‑oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.

Individuals seeking employment at Schonfeld are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

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.