Alpha Researcher
Defuse Labs develops NEAR Intents, an intent-driven transaction framework for AI-powered cross-chain interactions. It connects AI agents, services, smart contracts, decentralized applications, and financial applications through secure, scalable infrastructure.
About Defuse Labs
Defuse Labs is a deep-tech company operating at the intersection of AI, cryptography, decentralized finance, and blockchain interoperability. It designs intent-driven liquidity layers and develops NEAR Intents, a transaction framework that automates complex cross-chain operations, enabling autonomous agents, smart contracts, and decentralized services to execute transactions efficiently and securely. Its offering serves AI agents, blockchain services, decentralized applications, and financial applications requiring cross-chain liquidity and automation.
Skills
About the Role
Research, test, and refine quantitative trading strategies across on-chain and cross-chain markets. Build signal-generation, alpha-discovery, performance-attribution, analytical, simulation, and execution tooling; translate research into production systems; monitor market and portfolio performance; optimize liquidity; and identify new market opportunities.
Requirements
- 3+ years of experience in quantitative research, algorithmic trading, market making, or systematic investing; 7+ years for the Senior level.
- Strong background in mathematics, statistics, computer science, engineering, or a related quantitative field.
- Experience developing and deploying systematic trading strategies in crypto or traditional financial markets.
- Strong TypeScript programming skills; Rust, Python, or Go are a plus.
- Deep understanding of market microstructure, execution algorithms, liquidity dynamics, and risk management.
- Experience working with large datasets and building analytical pipelines.
- Ability to collaborate with software engineers and protocol developers.
- Ability to translate research into profitable strategies.
- Excellent communication skills for technical and business audiences.
- Experience with alpha generation or signal discovery engines is a plus.
- Knowledge of MEV, cross-chain execution, and decentralized exchange infrastructure is a plus.
- Experience with high-frequency or low-latency trading systems is a plus.
- Familiarity with AI and machine learning techniques applied to quantitative trading is a plus.
- Experience operating market-making or liquidity provision strategies is a plus.
- Contributions to open-source quantitative or blockchain infrastructure projects are a plus.
- Experience with Apache Airflow and dbt is a plus.
- Basic understanding of ELT and ETL workflows is a plus.
Responsibilities
- Design game-theoretical models for interactions among the NEAR Intents protocol, distribution channels, market makers, and end users.
- Research, design, test, and iterate quantitative trading strategies across on-chain and cross-chain markets.
- Build frameworks for signal generation, alpha discovery, and performance attribution.
- Develop systematic trading and liquidity optimization capabilities.
- Translate research into production-grade systems with protocol engineering.
- Develop analytical infrastructure, simulation environments, and tooling for strategy research and execution.
- Monitor market conditions, execution quality, and portfolio performance to improve trading models.
- Identify market opportunities and monetization strategies with product and ecosystem teams.
- Contribute to metrics, reporting, and experimentation frameworks.
