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Tower Research Capital

Trades financial markets with computer models

Software Engineer - Trading Systems, C++

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USAHybrid

About the Job

Requirements

  • A degree in Computer Science, Engineering, Mathematics, Physics, or a related technical field is required.
  • A strong foundation in algorithms, data structures, distributed systems, and software design is required.
  • Strong programming skills in C++ are required.
  • An interest in financial markets, systematic trading, and quantitative research workflows is required.
  • Experience building high-performance systems, data-intensive applications, or low-latency software is required.
  • The ability to collaborate with quantitative researchers, traders, and engineers to solve complex technical and analytical problems is required.
  • Strong analytical and problem-solving abilities focused on correctness and performance are required.
  • The ability to manage multiple projects and priorities in a fast-paced environment is required.
  • Strong communication skills and a collaborative mindset are required.

Responsibilities

  • Architect and evolve the trading platform to support quantitative research, simulation, and production trading needs, especially market data and execution systems.
  • Partner with quantitative researchers, traders, and software engineers to design, implement, and deploy systematic trading strategies.
  • Design and develop high-performance trading infrastructure for collecting market data, processing trading signals, and routing orders to exchanges worldwide.
  • Build frameworks and tools that enable researchers to prototype, backtest, analyze, and deploy trading strategies rapidly.
  • Develop scalable systems that provide efficient access to live and historical market data for research, simulation, and production.
  • Collaborate with researchers to turn quantitative models into robust, maintainable production systems.
  • Lead development efforts across the strategy lifecycle, from research tooling and data infrastructure through production deployment and monitoring.
  • Optimize trading and research systems through low-latency software design, network programming, performance analysis, and systems-level engineering.
  • Create tools and analytics to identify market patterns, evaluate strategy performance, and improve trading decisions.
  • Build risk management, monitoring, and performance attribution systems for researchers and traders.
  • Investigate production trading behavior and work with strategy teams to diagnose performance, execution, and market data issues.
  • Contribute to the architecture of shared platforms that improve productivity across research, development, and trading teams.

Desired Qualifications

  • Experience with Python is strongly preferred.
  • Experience with market data systems, exchange connectivity, or electronic trading platforms is desirable.
  • Experience building research platforms, backtesting systems, simulation frameworks, or quantitative analytics tools is desirable.
  • Familiarity with statistical analysis, machine learning, or quantitative modeling techniques is desirable.
  • Experience working in Linux environments and developing distributed systems is desirable.
  • Knowledge of Python or Rust is desirable.

About the Company

Tower Research Capital

Trades financial markets with computer models

Tower Research Capital trades financial instruments with computer models and supplies liquidity, or ready buying and selling prices, to other market participants. Its researchers test strategies against historical data before deploying them through a platform built largely in-house. The platform combines market data, order routing and risk controls, letting traders act on signals across stocks, futures, options and currencies. It earns trading profits by taking positions for its own account, and its liquidity businesses trade directly with counterparties rather than managing their investments. Tower was founded in 1998 and is headquartered in New York City.

Company size
1,001-5,000
Company stage
Not listed
Total funding
$116.1M
Headquarters
New York City, New York
Founded
1998

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