• Architect and build high-performance AI agent infrastructure from the ground up • Design and implement on-chain coordination systems (funding mechanisms, governance, research incentives, token flows) • Build fault-tolerant backend services for agent orchestration, data pipelines, and integration with external systems (cloud labs, bio-databases, CROs) • Optimise system performance, throughput, and reliability under real-world research workloads • Lead technical decisions around system design, data models, and scaling strategy • Collaborate closely with product and science teams to translate research requirements into production systems • Establish best practices for code quality, testing, observability, and incident response • Mentor other engineers as the team grows