Job Description

We are currently looking for our future Senior Software Innovation Engineer to join our R&D department, more specifically our Data Science & AI Innovation team. This role is based at the VIC (Verkor Innovation Center) in Grenoble, France.
As such, you sit at the intersection of business, product, and digital platforms. The role is responsible for transforming business-driven platform ideas into technically validated, prototype-backed software solutions that are ready for industrialization by digital/IT teams. The role focuses on early stages of platform design, hands-on prototyping, and technical feasibility validation, ensuring that initiatives entering the digital pipeline are clear, realistic, and production-aware. It ensures digital teams receive well-defined, technically credible inputs to accelerate time-to-value. It further reduces ambiguity, rework and misalignment between business and digital.

Main responsibilities :

• Work closely with business and R&D stakeholders to understand use cases, constraints and value drivers
• Design high-level platform architecture aligned with enterprise standards
• Build working technical prototypes to validate integrations, data flows and deployment models
• Package prototypes so they are reproducible and sharable with digital/IT
• Document architecture of the prototype, APIs, assumptions, risks and open points
• Act as a technical single point of contact from ideation to handover.

Requirements :

• Msc or Engineering diploma
• Minimum of 6 years of experience
• English and French are both mandatory
• Strong understanding of cloud-native platforms and modern digital architectures
• Ability to design high-level platform architectures (Microservices, APIs, event-driven)
• Knowledge on enterprise integration patterns (REST, messaging, data pipelines)
• Ability to build working technical prototypes
• Proficiency in atleast two backend languages, Python, Java, Node.js
• Ability to develop APIs, data processing flows
• Familiarity with SQL & NoSQL databases
• Hands-on experience with docker
• Working knowledge on Kubernetes
• Understanding CI/CD principles
• Familiarity with infrastructure as code concepts
• Understanding of production readiness criteria