About the role
We are looking for a Senior Software Development Engineer to build and maintain backend systems for systematic trading, market alerts, strategy research, back testing, and financial data workflows.
This is not a pure quant researcher role and not a generic CRUD backend role. The ideal candidate sits between backend engineering, quant development, and platform engineering: someone who can build reliable production services, understand trading/research workflows, optimize Python systems, and work closely with researchers, traders, and product engineers.
We especially value engineers with demonstrated depth in the Python ecosystem, including open-source contributions to typing, testing, data, or infrastructure libraries.
Responsibilities
You will:
- Build and maintain Python backend services for systematic trading products, automated market alerts, and research workflows.
- Design APIs and internal services communications both synchronously via REST APIs and asynchronously using message buses.
- Build data pipelines, workers, schedulers, and event-driven services for market data, trading signals, and strategy evaluation.
- Own and improve internal back testing infrastructure in terms of reliability and scale.
- Work with quant researchers and trading stakeholders to turn strategy ideas into robust backend systems.
- Optimize performance-critical Python workflows through concurrent/parallel programming.
- Design and maintain authentication and authorization systems for internal services.
- Improve engineering standards across the team: testing, type hints, linting, formatting, structured logging, CI, code review, and internal libraries.
- Mentor engineers and contribute to architecture while remaining hands-on with code.
Requirements
- 4+ years of professional software engineering experience.
- Bachelor's degree in Physics and Applied Mathematics.
- Strong production experience with Python.
- Experience building backend services, APIs, workers, or internal platforms.
- Experience with queues, scheduled jobs, async processing, or event-driven systems.
- Experience with modern Python web/database frameworks such as Fast API and SQL Alchemy.
- Strong relational database understanding, including schema design, query optimization, and ORM usage.
- Strong understanding of concurrency and parallelism in Python: asyncio, multiprocessing, multithreading, vectorized computations.
- Strong software engineering fundamentals: testing, CI/CD, maintainability, observability, and code quality.
- Ability to lead technical projects and mentor other engineers.
- Comfortable working in a small, high-ownership engineering team.
- Degree in mathematics, physics, computer science, engineering, or a related quantitative field.
- Willingness to work 6 days per week Monday to Saturday from 9 am to 6 pm and be able to meet tight project window.
Strong pluses
- Open-source contributions to major Python ecosystem projects, especially libraries involving testing, typing, data processing or relational databases.
- Deep familiarity with the Python programming language, including language-specific quirks around typing, stubs, and type-checkers such as mypy or pright.
- Experience with Python data orchestration tools such as Airflow or Prefect.
- Experience with Python data processing libraries such as Pandas, Polars, Dask.
- Experience with RabbitMQ, Redis or similar technologies.
- Experience with Docker and Kubernetes.
- Experience building authentication/authorization systems such as OAuth2 and OIDC.
- Experience with financial systems, trading infrastructure, market data, back testing, market risk management systems, or quant research tooling.