Software Engineer Network Automation, Data Center Fabrics

12 ago - Italia
MISTRAL

About MistralMistral provides full‑stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high‑stakes industries like finance, manufacturing, defense, healthcare, and the public sector—co‑creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low‑ego and team‑spirited.

Se è interessato/a a candidarsi per questo lavoro, la preghiamo di assicurarsi di soddisfare i seguenti requisiti, elencati di seguito.
The RoleAs a Software Engineer, Network Automation – Data Center Fabrics, you will design and build systems for operating large‑scale networks within our data centers.
Apply deep networking expertise to leaf‑spine architecture, automation, testing,



and production troubleshooting across Ethernet switching, IP routing, BGP, EVPN/VXLAN, and VRFs. This is a hands‑on role for a networking expert who is also comfortable building production software. Go and Kubernetes experience are helpful but not required; strong engineering fundamentals and network automation experience matter more.
What You Will Do
- Design and evolve leaf‑spine underlays, EVPN/VXLAN overlays, and tenant connectivity for multi‑tenant AI infrastructure.
- Translate data‑center fabric requirements and safety properties into clear APIs, data models, validation, and automation.
- Build reliable control‑plane software that reconciles desired and observed network state.
- Design safe change workflows with validation, dry runs, atomic updates, observability, and failure recovery.
- Integrate with data‑center switch operating systems and management APIs while maintaining vendor‑neutral abstractions where practical.

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