Manager, Applied AI Engineering, Life Sciences (Beneficial Deployments)
Core
Lead a team of Applied AI Engineers to build deterministic tools, connectors, and agent workflows that integrate frontier LLMs into the scientific and regulatory workflows of pharma and biotech organizations.
Role type
Manager, Applied AI Engineering (Life Sciences)
Builds
Production-grade agent integrations, data connectors, and evaluation harnesses for biological data and scientific workflows.
Domain
Life Sciences / Biotechnology / Pharma / Applied AI
Deliverable
production ML models | product features
Required skills
Engineering leadership, hands-on ML/AI engineering, domain expertise in pharma/biotech/bioinformatics, customer-facing technical delivery, LLM/agent system architecture, data infrastructure design, responsible AI deployment.
Preferred skills
Experience with MCP servers, scientific computing pipelines, scaling customer-facing technical teams.
Technologies
Large Language Models, Agents, MCP (Model Context Protocol), Python, Data Infrastructure
Responsibilities
Hire and coach a team of Applied AI Engineers; own technical success with strategic pharma/biotech partners; review and contribute to prototypes and agentic workflows; build deterministic tools and connectors for biological data; translate field learnings into product roadmap; set standards for responsible AI deployment in dual-use domains.
Seniority
Manager, hands-on IC leadership
