AI Engineer

Parallel; Paris; Sur place; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Parallel is building AI agents to help healthcare facilities automate administrative processes, starting with medical coding. As a Founding AI Engineer, you will design and implement LLM-powered systems for automating medical coding and build agent-based workflows tailored to clinical operations.

You will collaborate with doctors, hospital IT, and the CTO to integrate outputs with user-facing apps, ensure secure data ingestion pipelines, and advance the AI roadmap.

Qualifications

• 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

Responsabilités

• 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

Connaissances

5+ years of ML/AI production

LLMs/NLP

Python/Node.js

TypeScript/NestJS/Express

Data security (healthcare)

Outils

Hugging Face

LangChain

PyTorch

Description du poste

Overview

At Parallel, we build AI agents to help healthcare facilities automate their administrative processes, starting with medical coding. We aim to reduce the 25% of healthcare spending lost to manual, repetitive work by providing AI agents that operate inside existing hospital tools with no integrations or disruption. Our first agent automates end-to-end coding workflows to free up time for medical staff to focus on patients. We launched in 2024 with backing from investors including Frst, Y Combinator, Hexa, Kima Ventures, and Better Angle.

The future of healthcare isn’t just digital — it’s automated. Come help us build it.

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 is passionate about the ongoing AI revolution, action-oriented, autonomous, and ambitious. You are the ideal candidate if you have:

Qualifications

• 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