Digital Network Architect

3 days ago

Amrāvati, Maharashtra, India beBeeAutomation Full time ₹ 80,00,000 - ₹ 1,40,00,000
Job Description\helpers will design, implement, and optimize automation solutions for large-scale datacenter networks that support AI/ML workloads. This involves developing network automation frameworks, building Ansible playbooks, and creating Python-based automation scripts to integrate with APIs, orchestration platforms, and monitoring systems.">
  • Collaborate with cloud infrastructure, network engineering, and DevOps teams to deliver seamless provisioning and scaling of GPU/TPU clusters.
  • Document automation processes, workflows, and operational guidelines for the datacenter network.
  • Stay updated on emerging technologies in network automation, SDN, and private cloud networking.
Required Skills & Qualifications
  1. Expertise in Ansible (playbook development, dynamic inventory, custom modules) for large-scale network automation.
  2. Strong proficiency in Python for scripting, API integrations (REST, NETCONF, gNMI), and device interaction (e.g., NAPALM, Netmiko, Paramiko).
  3. Hands-on experience with high-performance datacenter networking devices (Cisco Nexus, Arista, Juniper, Mellanox/NVIDIA Networking).
  4. Knowledge of Linux / Windows / Hypervisor OS core networking, including:
  • Network stack configuration (sysctl tuning, TCP/UDP parameters).
  • NIC bonding, SR-IOV, DPDK, and kernel bypass techniques.
  • VLANs, routing tables, MTU adjustments, jumbo frames.
  • Performance tuning for HPC/AI workloads.
Deep understanding of networking concepts including BGP, EVPN-VXLAN, MPLS, QoS, and leaf-spine architectures.Experience in Private Cloud environments with a focus on supporting HPC/AI workloads.Familiarity with CI/CD pipelines (GitLab, Jenkins) for deploying automation at scale.Knowledge of network observability, telemetry, and streaming protocols (gRPC, sFlow, SNMP, InfluxDB, Prometheus).

 

Good to Have
  1. GoLang experience for building scalable and high-performance automation tools.
  2. Familiarity with Infrastructure-as-Code (IaC) tools like Terraform or Pulumi.
  3. Exposure to Kubernetes networking (CNI plugins) and containerized workloads.
  4. Understanding of AI/ML workload characteristics and their impact on network design and performance.
  5. Experience with SDN solutions (e.g., Cisco ACI, VMware NSX, NVIDIA Cumulus).

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