AI Engineer

Parallel; Paris; Sur place; EUR 95 000 - 140 000; Plein temps

Résumé du poste

Parallel is seeking a Founding AI Engineer to shape core AI architecture and strategy in a hospital setting. You will own end-to-end AI features, from research to production, collaborating with the CTO and founding team to deploy agent-based workflows and data pipelines that improve patient care.

You will work with Python/Node.js, TypeScript backends, and modern ML libraries to deliver production-ready AI systems while prioritizing data security and scalable infrastructure.

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).
• Familiarity with backend services (Node.js/TypeScript) and data infrastructure is a strong plus.

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 (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

ML/AI in production

LLMs & NLP

Python

Node.js

TypeScript

Backend services

Data security

Ownership

Prototype to product

Outils

Hugging Face

LangChain

PyTorch

NestJS

Express

Postgres

Terraform

Docker

Kubernetes

GitHub Actions

Description du poste

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