Full Stack Engineer (Los Altos)

Company OverviewCheiron is a Stanford-founded AI company building an AI-native operating system for the pharma, biotech, and broader life sciences industry.Since launching in **, we’ve rapidly grown our global user base.In Korea, we reached 22% of industry users within six months and are now used across 200+ pharma and biotech companies as we continue to scale quickly.About the RoleWe’re looking for a Full Stack Engineer, Applied AI to help build Cheiron’s core product and infrastructure.This role spans the full stack - backend systems, AI workflows, RAG and search pipelines, APIs, and the customer-facing product itself.You won’t own just one slice; you’ll work deeply across the product and systems and solve whatever problems need solving.We build products that run in real customer environments - not research demos or prototypes.We’re looking for a hands?on builder who can quickly structure ambiguous problems and turn them into highly polished products.You don’t need to be an AI researcher or a life sciences domain expert, but we care deeply about strong engineering fundamentals and real experience designing, building, and operating LLM systems.What You’ll Do- Design and build backend services on Python, FastAPI, and Postgres- Build applied AI workflows using the OpenAI API, LangGraph, vector DBs, and search systems- Develop ingestion, indexing, and search pipelines for life sciences data, including academic papers, clinical, regulatory, safety, and patent sources- Build customer-facing features end to end, from the data model to the API to the React/TypeScript frontend- Build systems that ground AI-generated outputs in source data with traceable, verifiable citations so they can be trusted in real pharma and biotech work- Work directly with founders, domain experts, and early customers, owning outcomes rather than just closing ticketsRequirements- 2+ years of experience shipping production software end to end- Strong backend engineering fundamentals and experience designing APIs, databases, and services- Hands?on production experience with AI?driven systems such as LLMs, agents, RAG, and vector DBs- Full-stack range, comfortable working through the frontend with React and TypeScript- The drive to set your own priorities and ship quickly, even when specs are incomplete- Active use of AI coding tools such as Claude Code and CursorNice to Have- Hands?on experience designing and operating LangGraph, agent frameworks, or RAG systems in production- Experience with vector DBs, semantic search, and knowledge graphs- Experience building enterprise SaaS, or pharma, biotech, or healthcare products- Familiarity with life sciences domain data such as academic literature, clinical trials, regulatory documents, and patents- Experience at a seed or early-stage startupBenefits & Perks- 401(K) retirement plan- Health insurances (Medical/Dental/Vision)- Meal allowance (Lunch, Dinner)- Transportation support for early starts and late nights- In?office snack bar and additional commuting and work travel support#J-***-Ljbffr

We’re looking for a hands?on builder who can quickly structure ambiguous problems and turn them into highly polished products. You don’t need to be an AI researcher or a life sciences domain expert, but we care deeply about strong engineering fundamentals and real experience designing, building, and operating LLM systems.What You’ll Do- Design and build backend services on Python, FastAPI, and Postgres- Build applied AI workflows using the OpenAI API, LangGraph, vector DBs, and search systems- Develop ingestion, indexing, and search pipelines for life sciences data, including academic papers, clinical, regulatory, safety, and patent sources- Build customer-facing features end to end, from the data model to the API to the React/TypeScript frontend- Build systems that ground AI-generated outputs in source data with traceable, verifiable citations so they can be trusted in real pharma and biotech work- Work directly with founders, domain experts, and early customers, owning outcomes rather than just closing ticketsRequirements- 2+ years of experience shipping production software end to end- Strong backend engineering fundamentals and experience designing APIs, databases, and services- Hands?on production experience with AI?driven systems such as LLMs, agents, RAG, and vector DBs- Full-stack range, comfortable working through the frontend with React and TypeScript- The drive to set your own priorities and ship quickly, even when specs are incomplete- Active use of AI coding tools such as Claude Code and CursorNice to Have- Hands?on experience designing and operating LangGraph, agent frameworks, or RAG systems in production- Experience with vector DBs, semantic search, and knowledge graphs- Experience building enterprise SaaS, or pharma, biotech, or healthcare products- Familiarity with life sciences domain data such as academic literature, clinical trials, regulatory documents, and patents- Experience at a seed or early-stage startupBenefits & Perks- 401(K) retirement plan- Health insurances (Medical/Dental/Vision)- Meal allowance (Lunch, Dinner)- Transportation support for early starts and late nights- In?office snack bar and additional commuting and work travel support#J-*****-Ljbffr

Company OverviewCheiron is a Stanford-founded AI company building an AI-native operating system for the pharma, biotech, and broader life sciences industry.Since launching in **, we’ve rapidly grown our global user base. In Korea, we reached 22% of industry users within six months and are now used across 200+ pharma and biotech companies as we continue to scale quickly.About the RoleWe’re looking for a Full Stack Engineer, Applied AI to help build Cheiron’s core product and infrastructure.This role spans the full stack - backend systems, AI workflows, RAG and search pipelines, APIs, and the customer-facing product itself. You won’t own just one slice; you’ll work deeply across the product and systems and solve whatever problems need solving.We build products that run in real customer environments - not research demos or prototypes.