Quant Developer
Wavebridge provides institutional-grade digital asset finance solutions.
Projects
About Wavebridge
Wavebridge is a financial technology company that bridges traditional finance with the digital asset frontier. It provides secure, seamless, and scalable solutions for institutional clients, including crypto-infrastructure that evolves with market and regulatory changes. The company's services encompass brokerage with support for blockdeals, custody and safekeeping, and a comprehensive digital asset management platform offering tax and accounting support, balance and P&L reporting, and detailed transaction analysis. Additionally, Wavebridge offers the "Wave Pricing Engine," a tool for accurately pricing derivatives and managing risk. The company is a registered Virtual Asset Service Provider (VASP) in Lithuania, adhering to AML and CTF regulations.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop and improve options and structured-product trading systems, backtesting and simulation engines, and pricing and risk-management logic. You will automate structured and DeFi strategies with traders, build market-data and ML feature pipelines, and lead the design, deployment, and operation of AI/ML infrastructure for trading.
Requirements
- Python
- C++
- Interest in and understanding of cryptocurrency markets, including CEX, DEX, DeFi, and stablecoins
- Relevant experience in at least one of trading-system implementation, trading logic, structured-product valuation, or AI/ML system development
- Basic English communication skills
Responsibilities
- Develop and enhance options and structured-product trading systems
- Design and maintain backtesting and simulation engines
- Implement pricing models and risk-management logic, including Delta, Vega, and Gamma
- Automate structured and DeFi strategies with traders
- Build and analyze market-data and ML feature pipelines using on-chain, exchange, and alternative data
- Develop algorithmic-trading infrastructure, including order management, execution engines, and monitoring
- Develop trading strategies
- Develop LLM and NLP pipelines for news, on-chain, and alternative data
- Lead the design, implementation, and operation of AI/ML infrastructure for trading
Hiring Process
Document screening > first interview with practitioners, including a 5–10 minute personal-project presentation > second executive interview > compensation discussion and joining coordination > final offer. Pre-employment identity verification is conducted.