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Tower Research Capital

Software Engineer

New York$130k–$170kfull-timemidAdded today

About this role

Tower Research Capital seeks a Software Engineer to build and maintain internal tools, data workflows, and operational applications that support the firm's trading platform. You'll develop Python-based services, design data pipelines, and create AI-enabled tools including an internal chatbot for operational support, working across a full stack from backend APIs to frontend interfaces.

What you'll do

  • Build and maintain internal tools, data workflows, and operational web applications
  • Develop Python services, automation scripts, and data processing jobs for business users
  • Design data ingestion, transformation, validation, and reconciliation workflows
  • Build AI-enabled internal tools and chatbot using LLM patterns like RAG and function calling
  • Write SQL queries for reporting, investigation, and operational analysis
  • Debug and improve reliability, observability, and test coverage across systems

What they're looking for

  • Python programming
  • SQL and relational databases
  • Data workflow design (ETL, reconciliation, validation)
  • Backend API development and frontend integration
  • Git-based workflows and CI/CD pipelines
  • Linux/Unix environments
  • AI/LLM integration and RAG patterns
  • Web application development

Benefits

  • Work on high-performance trading infrastructure
  • Collaborate with world-class engineering and trading talent
  • Access to cutting-edge technology and continuous investment in tools
  • Results-oriented, stimulating work environment
  • Discretionary bonus eligibility
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Tower Research Capital

Tower Research Capital builds high-performance quantitative trading systems and infrastructure, serving traders and researchers with low-latency platforms for market data, strategy execution, and order management. The company is hiring software engineers, quantitative developers, and infrastructure specialists to design scalable systems, optimize trading platforms, and enhance development tooling.

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Likely interview questions

  • Describe your experience building data workflows (ETL, validation, reconciliation) in production environments—what challenges did you encounter and how did you solve them?
  • Walk us through a time you debugged a complex issue across code, database, APIs, and deployment environments. How did you approach it?
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