About the role
Design, build, and operate large-scale network fabrics to support GPU clusters and high-performance computing workloads. Manage the full lifecycle of network infrastructure from architecture design through deployment, optimization, and operational support.
What they look for
Requirements
Requires over 10 years of core networking experience with deep expertise in BGP, OSPF, EVPN, and VXLAN protocols. Candidates must possess strong proficiency in Python scripting, infrastructure automation, and hands-on experience with major network operating systems.
Full description
About the Role
We're building AI/HPC infrastructure that powers the next generation of high-performance computing. As a Network Engineer, you'll responsible to design, build, and operate large-scale network fabrics that support GPU clusters, HPC workloads, and mission-critical AI systems. You'll engage across the full lifecycle—from requirements gathering and architecture design through deployment, optimization, and operational support. This is hands-on infrastructure work.
What you'll be doing:
· Design and deploy EVPN-VXLAN Clos/Leaf-Spine Ethernet fabrics and InfiniBand networks for high-performance computing environments
· Configure and troubleshoot BGP, OSPF, VXLAN, and EVPN protocols across multi-vendor platforms (Arista, Cumulus, SONiC, Juniper, Cisco)
· Deploy lossless fabrics (Ethernet and InfiniBand) which use RDMA technologies for high-performance computing.
· Build and validate network topologies in lab environments using simulation tools (NVIDIA Air, GNS3, EVE-NG)
· Develop and optimize network automation solutions using Python and Ansible for network infrastructure
· Support operational excellence: monitor network health, troubleshoot production issues, and coordinate with vendors for rapid resolution
· Create comprehensive documentation, operational runbooks, and knowledge bases for customer support and knowledge transfer
What we need to see:
Core Networking (10+ years)
· Deep expertise in TCP/IP stack, Layer 2/3 switching, routing, and data center architecture
· Expert-level knowledge of BGP, OSPF, EVPN, and VXLAN (5+ years hands-on experience)
· Strong understanding of Clos/Leaf-Spine fabric design and multi-tier network architectures
· Advanced network troubleshooting using packet sniffers, analysis tools, and diagnostic techniques
· Hands-on with at least one network operating system viz. Arista EOS, Cumulus Linux, Cisco, Nokia SR Linux etc.
· Configuration, testing, validation, and issue resolution on these platforms in production environments
· Ethernet lossless networking concepts (PFC, ECN, DCQCN, RoCEv2)
· InfiniBand networks for HPC: configuration, troubleshooting, and performance optimization in large-scale environments
· Linux networking knowledge
Automation & Infrastructure-as-Code
· Expert-level Python scripting for network automation and tooling
· Extensive experience with Ansible, Salt, or equivalent infrastructure automation frameworks
· Ability to develop CI/CD pipelines for network infrastructure provisioning and testing
· Git version control and Infrastructure-as-Code practices
· Lab environment simulation and topology validation using NVIDIA Air, GNS3, EVE-NG, or similar tools
Ways to stand out from the rest:
· Networking certifications: Cisco, Arista, Nokia, Nvidia or equivalent
· Linux Certifications
· Kubernetes and Docker; container networking
· Cloud networking: AWS, GCP, Azure; hybrid cloud and on-premises integration
· Personal GitHub repository with Python examples and evidence of coding expertise
Minimum Qualifications:
Bachelor’s degree in computer science, Electrical/Computer Engineering, Physics, Mathematics, or related field (or equivalent industry experience) years of networking fundamentals and data center architecture · 5+ years of hands-on EVPN/BGP/VXLAN experience · Proficiency in at least one major platform (Arista, Cumulus, SONiC, Juniper, Cisco) · Production troubleshooting experience.
Soft Skills:
· Strong problem-solving and debugging abilities
· Ownership mindset with accountability for deployment quality and customer success
· Cross-functional collaboration with other teams
· Proactive approach to continuous learning and staying current with AI infrastructure trends
· Strong documentation and presentation skills, with ability to defend design decisions in peer reviews.
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