Product Manager (Artificial Intelligence)

Join our team as a Product Manager (Artificial Intelligence) and play a key role in building production-grade agentic AI systems for complex, data-intensive environments. In this hybrid role, you will define what gets built and actively build it, contributing to the full AI product lifecycle from discovery and requirements to deployment and iteration. You will design, build, and iterate on LLM-powered agentic workflows, translate business and user needs into actionable product requirements, and manage the post-launch product lifecycle. Additionally, you will collaborate with governance teams, engage with internal stakeholders, and support demos and presentations of prototypes and new capabilities.

- Contribuer à l'ensemble du cycle de vie du produit AI : découverte, définition des exigences, développement, test et déploiement. - Concevoir, construire et itérer sur des flux de travail agentiques alimentés par des LLM pour des cas d'utilisation complexes et intensifs en données. - Définir et surveiller les indicateurs de performance du produit et les critères d'acceptation pour les sorties AI en production.

- Experience evaluating and testing AI outputs — defining acceptance criteria, identifying edge cases, and working with engineering teams to resolve model or integration issues - Comfortable working across technical and commercial stakeholders — able to translate product decisions clearly for engineering teams and client-facing audiences alike - Demonstrated hands-on experience building with LLMs and/or agentic frameworks — shipped products or features preferred over academic work - Working knowledge of how large language models and agentic systems behave in production - including tool use, prompt design, orchestration patterns, output variability, and failure modes - BA, BS, or Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience - Experience with real-time or near-real-time data systems, with a natural sensitivity to latency, throughput, and cost trade-offs - Exposure to AI partner platforms or ecosystems in a product, technical, or commercial capacity is an advantage - Ability to write clear product requirements and define, review, and challenge technical specifications without requiring engineering support - 5+ years of experience spanning software or ML engineering and product development, or a closely related combination — we value technical depth and product ownership in equal measure - Familiarity with responsible AI principles — including data quality, model performance monitoring, and bias considerations — and their implications for product design in regulated environments - Solid Python skills and familiarity with APIs, data pipelines, and cloud infrastructure