AI Engineer

At Parallel, we build AI agents that help healthcare organizations automate their administrative processes and unlock additional revenue, starting with medical coding. Today, up to 25% of healthcare spending is lost to manual, repetitive administrative tasks. Legacy software hasn't helped: it has made work slower, more complex and more frustrating for care teams. We believe AI agents can change this. Our technology combines large language models with system-level automation to do real work inside existing hospital tools. No integration, no disruption. Our first agent automates coding and frees up time for medical teams to focus on patients. We launched in 2024 and already have 800+ customers and a team of 30+ people. We are backed by top-tier investors (Index Ventures, Y Combinator, Hexa, Frst, Kima Ventures, Better Angle and the CEO of Mistral AI), and this is just the beginning. The future of healthcare isn't just digital, it's automated. Come help us build it! CONTEXT AI systems that can ease the administrative burden on hospitals only have value if they run in production, in real hospitals, on sensitive health data. That is the core of this role. You won't just write models: you will shape Parallel's AI architecture, define our machine learning strategy and integrate intelligent systems directly into hospital workflows. You will work with the CTO and the founding team, with a very high level of autonomy, from agentic LLM workflows to the way AI outputs reach doctors' tools. WHAT YOU'LL DO - Production LLM systems: design and deploy LLM-based systems that automate medical coding in real clinical environments. - Agentic workflows: build and evolve agent workflows suited to complex clinical operations. - Secure data pipelines: build secure, scalable data ingestion pipelines with hospital IT teams, compliant with health data security standards. - Product integration: integrate AI outputs into the applications used by doctors and hospital staff. - AI roadmap: define the AI roadmap with the CTO and own the full lifecycle of each AI feature: research, prototyping, evaluation, deployment and monitoring. In your first months, you will have taken ownership of our LLM systems and agentic workflows and shipped your first improvements in real clinical environments. You will have owned an AI feature end to end, from research to monitoring, through prototyping, evaluation and deployment. You will also have built or improved, with a hospital's IT team, a secure data ingestion pipeline compliant with health standards, and defined the AI roadmap for the coming months with the tech team. WHO YOU ARE - You have at least 3 years of experience working on applied ML/AI problems in production: systems that run, not just POCs. - You graduated from a top engineering school. - You have solid experience with LLMs and NLP, especially prompt engineering and/or fine-tuning. - You are proficient in Python or Node.js and have worked with ML libraries (Hugging Face, LangChain, PyTorch...). - You have a strong sense of ownership and know how to move quickly from prototype to product. - You are autonomous and action-oriented, comfortable in a fast-moving startup where you build the core of the product rather than execute tickets. - You care more about users' problems than about the number of features shipped, and you like being close to the product and its users. - Bonus: knowledge of backend services (Node.js/TypeScript) and data infrastructure. - Bonus: experience with sensitive or regulated data (healthcare, finance...). OUR VALUES - Play to Win: we're not here to just take part, deliver something "good enough" or simply enjoy the startup ride. We want to win. That means caring about results, moving fast and bringing the right intensity when it matters. - High Trust, High Standards: trust is our starting point. If you join us, it's because we believe you can own your scope and make good decisions. We don't want a company built on approvals, control and micromanagement. But trust comes with accountability: the more freedom you have, the higher the bar. - Low Ego, Hands-On: at Parallel, no one is above the work. No title, seniority or past success exempts anyone from getting involved in the actual work. Leading means taking responsibility, not distancing yourself from execution. - Don't Take Yourself Too Seriously: we take our mission very seriously, not ourselves. Building a company is intense. We want Parallel to remain a place where people enjoy spending time together, laughing, celebrating and giving energy to others. High standards and a good atmosphere aren't opposites: we want both. HIRING PROCESS 1. Call with the Hiring team (30 min) 2. Call with Chris, CTO (30 min) 3. Case study and interviews with Chris and Paul, the founders, at our office in Paris 2nd (2 hours) 4. Reference checks WHY JOIN US? - A rare opportunity: from day one, you shape Parallel's AI architecture and machine learning strategy, with a very high level of autonomy alongside the founders. - Real impact: your systems directly reduce burnout among hospital teams and give them back time for patients. - Cutting-edge projects that go to production: LLM and agentic systems deployed in real clinical environments, with the engineering rigor needed to make them reliable (end-to-end typing, automated best practices, fast iteration with tools like Cursor). - Real traction: seed and Series A ($20M with Index Ventures) closed in less than a year, 800+ customers and a team of 30+ people. - Strong investors and founders: Index Ventures, Y Combinator, Hexa, Frst, Kima Ventures, Better Angle and the CEO of Mistral AI; founders who come from Meta, McKinsey and Hublo. - A complete package: competitive salary and equity (BSPCE), Alan health insurance, Swile meal vouchers, Apple equipment, 50% of public transport covered. - A close-knit team: a team event every month and two offsites a year. - Our office: Paris 2nd arrondissement. - Flexibility: on average one day of remote work per week and one week of remote work per year. We care about who you are, not just what's on your CV. If you're drawn to what we're building but don't meet every requirement, we still want to hear from you. Studies show that women in particular tend to apply only when they meet 100% of the criteria. If that's you, please don't let that hold you back. We'd love to receive your application.