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At Parallel, we build AI agents to help healthcare facilities automate their administrative processes, starting with medical coding.
Today, up to 25% of healthcare spending is lost in manual, repetitive administrative work. Legacy software hasn’t helped, it’s made things slower, more complex, and more frustrating for care teams.
We believe AI agents can change that. Our technology combines Large Language Models with system-level automation to handle real work inside existing hospital tools. No integrations, no disruption.
Our first agent automates end-to-end coding workflows and frees up time for medical staff to focus on patients.
We launched in 2024, are backed by top investors (Frst, Y Combinator, Hexa, Kima Ventures, Better Angle), and we’re just getting started.
The future of healthcare isn’t just digital — it’s automated. Come help us build it !
Parallel in numbers📜 Started in Summer 2024
💪 Small team from top-tier companies (Meta, Lifen, Hublo, Ramsay)
💸 Raised 3.5M$ with Frst & Y Combinator
🏥 Already working with leading Hospitals and Clinics
As we scale, we're looking for a Founding AI Engineer to join us at this pivotal moment. You won’t just write models — you’ll help shape the core AI architecture, define our machine learning strategy, and embed intelligent systems directly into hospitals. This is a rare opportunity to build with high ownership, alongside a small and passionate team who cares deeply about craft, clarity, and impact.
You’ll work closely with the CTO and founding team on everything from agentic LLM workflows to data pipelines and AI-first product design. If you're excited by the idea of deploying real-world AI that improves patient care and reduces hospital burnout, we’d love to talk.
We are looking for a Founding AI Engineer to help us achieve our mission of reducing administrative workload in hospitals.
This is a full-time role focused on designing and deploying production-ready AI systems in real-world clinical environments.
Mission
As a Founding AI Engineer, you will:
Design and implement LLM-powered systems for automating medical coding
Build and iterate on agent-based workflows tailored to complex clinical operations
Collaborate on integrating AI outputs with user-facing apps used by doctors and hospital staff
Work closely with hospital IT to build secure and scalable data ingestion pipelines (adhering to health data security standards)
Partner with the CTO to define the AI roadmap and integrate state-of-the-art tools with robust backend infrastructure
Own the full lifecycle of AI features: research, prototyping, evaluation, deployment, and monitoring
We’re looking for someone who’s passionate about the ongoing AI revolution, action-oriented, autonomous, and ambitious. You are the ideal candidate if you have:
5+ years of experience working on applied ML/AI problems in production environments
Strong experience with LLMs and NLP, including prompt engineering and/or fine-tuning
Proficiency in Python or Node.js and experience with ML libraries (e.g. Hugging Face, LangChain, PyTorch, etc.)
Familiarity with backend services (Node.js/TypeScript) and data infrastructure is a strong plus
A deep sense of ownership and ability to move from prototype to product quickly
Experience working with sensitive or regulated data (healthcare, finance, etc.) is a bonus
Technical stack
Backend: Typescript with NestJS, Express, Prisma, Postgres
Frontend: React, TanStack, Tailwind
Data: Python & Node (for low level proxy servers)
Tools: Monorepo, Github, Github actions
Infra: AWS, Azure, Cloudflare, Docker, Terraform, Kubernetes
CI/CD: Github, Github Actions, Monorepo setup
Observability: Datadog
AI/ML: Hugging Face, LangChain
Engineering Mindset
Data security is our foundation, given our work with sensitive health data
We focus on solving user problems, not shipping features — deep product involvement is essential
Full type safety from database to UI
Rapid development with tools like Cursor
Automated best practices with eslint, Prettier, Jest, and TypeScript
We leverage the latest technologies and libraries but sometimes, old boring tech that does the job is what’s needed
Infrastructure should empower — not block — product iteration
Quick chat with our CTO Chris
AI/technical case study — ideally in person at our Paris office
Meeting with our CEO Paul
Drink to meet the team
Key Skills
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