4 дня назад
Product Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Product Engineer (AI): Building the Ops AI Platform, where internal teams create, evolve, monitor, and safely deploy AI agents for large-scale operational automation with an accent on product engineering, LLMs, tool calling, and internal-tools UX. Focus on designing reliable multi-agent systems, implementing human-in-the-loop safeguards, scaling automation from dozens to tens of thousands of daily tasks, and shaping the platform architecture from the ground up.
Location: Remote within France, Belgium, or Spain
Company
builds a prevention-focused healthcare insurance platform that integrates insurance, prevention, and care into one user experience.
What you will do
- Build the Ops AI Platform for creating, evolving, monitoring, and evaluating AI agents.
- Integrate AI agents into internal tools with context-aware interfaces for reviewing reasoning, actions, and follow-up instructions.
- Enable non-technical operations users to configure prompts, tools, datasets, tests, evaluations, and replayable workflows.
- Develop agent capabilities connected to internal business data, external servers, and web dashboards without APIs.
- Design safety and accuracy mechanisms, including stateful evaluation, progressive rollout, human-in-the-loop validation, and fine-grained permissions.
- Scale automation from dozens to tens of thousands of operational tasks per day while influencing architecture, mentoring engineers, and contributing to hiring.
Requirements
- 3+ years of experience in product engineering.
- Strong full-stack software engineering and systems architecture experience, with a strong backend focus.
- Fluent English; French is not required.
- Product-minded, self-directed, pragmatic, collaborative, and eager to learn and teach.
- Experience with traditional machine learning, LLMs, or MLOps is an advantage.
- Ability to work remotely from France, Belgium, or Spain.
Nice to have
- Experience with traditional machine learning, LLMs, or MLOps.
- Experience with tool calling, human-in-the-loop systems, internal tools UX, or multi-agent architectures.
Culture & Benefits
- Contract opportunity with a remote-first setup, flexible offices, sponsored coworking hubs, and home-office equipment support.
- Flexible working hours and vacation policy.
- MacBook Pro and additional professional equipment provided.
- Learning and training budget, including books and conference participation.
- Coaching from day one, extended parental leave, and country-specific commuter benefits.
Hiring process
- Applications are assessed for potential, curiosity, and fit with the engineering needs.
- The final engineering team may differ from the initially selected area based on where the candidate can have the most impact.
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