4+ years of technical experience as a software engineer, ML or research engineer, computational biologist, research scientist, or technical founder, with either production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale, or a track record of successfully applying AI to real scientific work in the lab or in research. Identify patterns across engagements, including what is hard about deploying AI in the life sciences such as heterogeneous data, auditability requirements, and the gap between a working prototype and a system that scientists trust, and contribute insights back to Product, Engineering, Research, and the broader Applied AI team, including feedback on the model capabilities and product features that would most accelerate discovery work.