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Translate product concepts into engineering-ready specifications for AI-native pharmaceutical CMC software. Define feature stories, acceptance criteria, edge cases, data models, API contracts, and AI quality standards. Collaborate with product, engineering, design, and life sciences teams to resolve ambiguity, validate regulatory content, and own product quality through delivery.

Own the detailed technical definition of product features, translating concepts into engineering-ready specifications with data models, API contracts, acceptance criteria, edge cases, and state transitions. Collaborate with product, engineering, design, and life sciences teams to resolve ambiguity, validate regulatory content, define correctness for AI features, and maintain quality through delivery. The role focuses on AI-native products for pharmaceutical CMC workflows and requires strong technical writing, architectural reasoning, and comfort working in ambiguous startup environments.

General internship for candidates proposing a specific contribution to Cheiron, an AI-native drug-program operating system. Interns identify a problem, define priorities and deliverables with a team, own projects through execution and handoff, communicate progress, incorporate feedback, and produce reusable work. The role is fully in-person in Los Altos, California, with semester or quarter availability of at least 20 hours weekly or full-time summer availability.

Translate product concepts into engineering-ready specifications for an AI-native biopharma platform. Break briefs into components, define feature stories, acceptance criteria, edge cases, data models, API contracts, and AI feature correctness standards. Collaborate with product, engineering, founders, and life sciences experts to resolve ambiguity, scope builds, and support implementation. The internship is fully in-person in Los Altos, California, with semester, quarter, co-op, or summer schedules.

Build and operate full-stack product and infrastructure for applied AI: backend services, AI workflows (LLMs, RAG, vector DBs), ingestion/indexing of life sciences data, APIs, and React/TypeScript frontends. Ensure AI outputs are grounded with verifiable citations and collaborate with founders, domain experts, and customers to deliver production-grade features.

Build and operate Cheiron's agent layer and backend systems: agent runtime/harness, tool-calling, sandboxed code execution, agent memory, vector DB/RAG/semantic search, large-scale ingestion and indexing of life sciences data, and APIs/services using Python, FastAPI, and Postgres. Ensure reliability, observability, and verifiable source-grounded outputs while working directly with founders and early customers.