Founding Engineer @Panora (backed by Hexa)

About Panora Panora is a B2B platform building AI-powered agents for insurance brokers, a highly regulated and operationally complex industry. Our ambition is to become the AI Operating System for brokers in Europe: automating high-friction, repetitive work while improving compliance, advisory quality, and client relationships. The product is already live with brokerage firms in France and Belgium, with AI agents in production (contract comparison, coverage analysis, compliance checks, Outlook/Word assistants, etc.). Founded by Diane - Ex-VC with strong operational background and Fabian - Repeat  founder, product-driven AI engineer, Panora is backed by Hexa (formerly eFounders), the startup studio behind 40+ tech companies such as Aircall, Spendesk, and Front, and is now entering a key phase of structuring and scaling the platform. At Panora, AI is not a side feature or a lab experiment - it is the core of the product. You will work hands-on with LLMs, agent-based systems, and production-grade AI pipelines, under real-world regulatory and reliability constraints from day one. The company is now entering a key phase of structuring and scaling the platform. About the Role As a Founding Engineer, you will join the founding team at the core of the product and technical strategy. You will work closely with the CTO and be involved across the entire product lifecycle: architecture, development, technical decision-making, and production readiness. This is a hands-on, high-impact role, with strong ownership and real influence on the company’s technical direction. Responsibilities Product & Engineering • Design, build, and ship core product features across AI agents, workflows, and integrations • Own technical architecture choices with scalability, security, and compliance in mind • Work closely with the founding team to turn product ideas into production-ready systems AI & Production Systems • Build and evolve AI pipelines (LLMs, RAG, agent-based systems) for real-world, regulated use cases • Ensure reliability, traceability, and explainability of AI outputs in production • Optimize performance, cost, and quality as the platform scales Ownership, Quality & Scalability • Own systems from build to production, with a strong focus on quality, reliability, and scalability • Support live deployments with regulated customers and anticipate industrialization challenges • Take part in core technical decisions and help shape how engineering is done at Panora (processes, standards, tooling)