Quantitative Developer

Remote Full-time
We are seeking experienced Quantitative Developers to develop the core systems powering our systematic crypto strategies. Our infrastructure combines machine learning, agent-based systems, and real-time data from across the crypto ecosystem. The role involves scaling research and trading platforms, developing intelligent agents, and enabling strategy automation across centralized and decentralized exchanges. This position is open to candidates with backgrounds in data engineering, ML systems, smart contract integration, or agent tooling. Responsibilities Build infrastructure for agent-powered systems that automate research, signal generation, and strategy management. Develop scalable, real-time data pipelines across CEXs, DEXs, and on-chain sources. Enable LLM-driven tooling and intelligent orchestration for crypto-native workflows. Work closely with researchers to implement signals, portfolio models, and execution logic. Integrate exchange APIs and blockchain data into a unified research and production environment. Design systems that are robust, modular, and built for multi-strategy, multi-venue deployment. Build dashboards and internal tools for portfolio analytics, scenario testing, and attribution. Qualifications Strong software engineering skills (Python preferred); experience with ML ops or distributed systems is advantageous. Background in research agent tooling, cloud-native infrastructure, or data-intensive backtesting systems. Solid understanding of crypto trading systems (spot, perpetuals, options) and multi-venue connectivity. Demonstrated ability to deliver production-grade systems supporting live trading environments. Experience with blockchain data parsing or exchange integrations. Familiarity with smart contract interaction, intent-based execution, or autonomous research infrastructure. Hands-on experience in crypto trading environments or building infrastructure for live strategy deployment. For our Candidate Privacy Policy, please visit https:// falcon.finance/candidate-privacy-policy.pdf
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