Backend Engineer, Applied Agents (Los Altos)

Cheiron; Los Altos; Presencial; EUR 50.000 - 75.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

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

Descripción de la vacante

Cheiron, based in Spain, is looking for a Backend Engineer for Applied Agents to help build an advanced AI-native operating system tailored for the pharma and biotech industries.

The ideal candidate will design and implement the backend systems that power cutting-edge agent functionalities. This role requires strong engineering fundamentals and experience with AI-driven systems.

Cheiron offers competitive benefits including health insurance and 401(K) retirement plans.

Formación

• 2+ years of experience shipping and operating production backend systems end to end.
• Strong backend engineering fundamentals and deep understanding of system reliability.
• Hands-on production experience with AI-driven systems such as LLMs, RAG, and vector DBs.

Responsabilidades

• Design, build, and operate Cheiron's agent layer.
• Develop backend services and APIs using Python and FastAPI.
• Construct large-scale ingestion, cleaning, and indexing pipelines for data.

Conocimientos

Backend engineering fundamentals

API design

Data modeling

AI-driven systems

Agent systems

Herramientas

Python

FastAPI

Postgres

AWS

Terraform

Kubernetes

Descripción del empleo

Company Overview

Cheiron is a Stanford-founded AI company building an AI-native operating system for the pharma, biotech, and broader life sciences industry.

Since launching in 2024, 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 Role

We’re looking for a Backend Engineer, Applied Agents to help build Cheiron's agent layer and the backend systems that power it.

Cheiron's agents don't just generate answers. They carry out multi-step tasks inside real drug development workflows, call tools reliably, execute code in sandboxed environments, retain context across multi-step work, and deliver verifiable results to users. You'll design and ship the agent runtime, harness, memory, and tool execution layers that make all of this possible.

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, build, and operate Cheiron's agent layer: agent runtime/harness, tool‑calling infrastructure, sandboxed code execution, agent memory, and the reliability and observability of multi‑step tasks
• Design and build backend services and APIs on Python, FastAPI, and Postgres
• Design and operate vector DB, semantic search, and RAG systems, and tune search quality and latency
• Build large‑scale ingestion, cleaning, and indexing pipelines for life sciences data, including academic papers, clinical, regulatory, safety, and patent sources
• 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 tickets

Requirements

• 2+ years of experience shipping and operating production backend systems end to end
• Strong backend engineering fundamentals: a deep understanding of API design, data modeling, databases, and system reliability
• Hands‑on production experience with AI‑driven systems such as LLMs, RAG, and vector DBs
• Practical understanding of how agent systems actually work: you've built — or at least deeply traced — agent runtimes, harnesses, tool calling, sandboxing, and memory
• The drive to set your own priorities and ship quickly, even when specs are incomplete
• A balance of fast shipping velocity and sound engineering judgment
• Active use of AI coding tools such as Claude Code and Cursor

Nice to Have

• (Most Important) Experience building an in‑house agentic harness: if you've designed and built internal tools or harnesses to boost your team's agentic development productivity, that's the strongest signal for us
• Hands‑on experience designing and operating LangGraph, agent frameworks, or RAG systems in production
• 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 deploying and operating production systems on AWS, Terraform, and Kubernetes, with a focus on reliability and observability
• Experience at a seed or early‑stage startup

Benefits & 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