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Salary
$165k – $190k per year
Location
Hybrid (New York, United States)
Seniority
Senior · 6+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 23, 2026.

Overview
Company
Impact
Profile match
Vola Dynamics is the market standard in institutional options analytics — volatility surface fitting, options pricing, Greeks, and risk — used by more than 50 of the world.

Vola Dynamics is the world's most sophisticated software and research company for advanced options analytics. Our volatility fitter and ultra-fast option pricers are the market standard, powering decisions at the world’s leading hedge funds, proprietary trading firms, market makers, and global banks.

We're seeking a data-oriented Software Engineer to play a pivotal role in developing our next-generation streaming data infrastructure from the ground up. This is a rare chance to design and build a modern trading analytics platform from scratch-one that will power cutting-edge applications built on Vola's advanced options analytics library.

We’re a small, tight-knit, highly technical team that values intellectual rigor, collaboration, and doing good work. You’ll take on broad responsibilities and contribute to work with real-world impact from day one. We help each other build, share ideas openly, and work together to get things done.

We're a hybrid team, in the office on Tuesdays and Thursdays.

What You'll Do

  • Design high-performance APIs: Design and implement robust, scalable, real-time and historical user-facing data APIs in C++, Python, and Rust.

  • Build powerful internal tools: Build powerful internal tools (GUIs, TUIs, etc.) for real-time command & control and meta-analytics that accelerate research and streamline the path from research to production.

  • Develop and maintain production data systems: Develop scalable systems to ingest, transform, and analyze real-time and historical options market data and deploy these on our distributed computing infrastructure.

  • Maintain our data processing library: Architect, build, and maintain the data processing library underpinning our streaming analytics.

  • Use AI: AI development tools (Claude Code, Codex) are a standard part of how we build software here, and we'll expect you to use them well.

  • Own our tech stack: Own and evolve a rapidly growing distributed infrastructure spanning bare-metal servers, self-hosted Kubernetes, and cloud services.

Who You Are

  • You earned a BS or MS degree in Computer Science, Physics, Mathematics, Data Science, Engineering, or another quantitative discipline.

  • You have between 2 years and 6 years of experience in relevant roles working on production data-oriented systems in Python.

  • You have experience designing, building, and maintaining scaleable, fault-tolerant user-facing APIs for data-focused services or systems.

  • You have hands-on experience deploying orchestration frameworks and containerization technologies such as Dagster, Airflow, Prefect, Docker, or Kubernetes.

  • You are skilled at understanding, transforming, analyzing, visualizing, and debugging large numerical datasets.

  • You are comfortable with using agent-driven development workflows to generate high-quality code.

  • You consistently apply software and data engineering best practices, including version control, automated testing, and thorough documentation.

  • You explain your thinking clearly, in code, review comments, design discussions, and writing.

  • You work well independently, and just as well as part of a small, hybrid team.

  • You hold current authorization to work in the US.

Our Stack

Python, C++, ClickHouse, Kubernetes, Kafka (Redpanda), Dagster, and Rust.

Nice to Have

  • Active open-source contributor in the Python, C++, or Rust data ecosystems.

  • Experience working with observability/tracing systems or production DevOps workflows.

  • Professional experience working in a systems language (C++, Rust, Java, C#, etc.)

  • Experience working on an options market making or derivatives infrastructure, or another quantitative finance background.

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