Senior Network Engineer

HCLTech; Bengaluru; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

HCLTech is seeking an experienced Network Engineer to own enterprise networking and Linux system support for AI/HPC/Kubernetes workloads in data centers and cloud environments.

You will drive production readiness, define SLO/SLI, implement observability, runbooks, DR/BCP blueprints, and lead safe release strategies including canary and blue/green deployments. Strong troubleshooting, RCA, and expertise in BGP/OSPF, InfiniBand, and cloud networking across AWS/Azure/GCP are required.

Qualifications

• Strong hands-on expertise in enterprise networking and Linux systems.
• Experience in data center / cloud networking operations (5–10 years).
• Ability to troubleshoot, perform performance tuning, and ensure operational stability of network and OS layers supporting AI/HPC/Kubernetes workloads.
• Knowledge of routing & switching (BGP, OSPF, VLANs) and load balancing; firewall basics a plus.
• Familiarity with cloud networking (AWS/Azure/GCP) and AI/HPC networking for distributed GPU workloads.

Responsibilities

• Define and maintain production readiness standards across platform, data, model, application, and security layers.
• Establish SLO/SLI frameworks for latency, availability, quality, safety, and drift; implement error budget policies.
• Maintain compliance mappings (ISO 27001, SOC 2, GDPR/DPDP, HIPAA where applicable).
• Author PRR checklists, runbooks/playbooks, and DR/BCP blueprints (RTO/RPO, multi-region/site failover).
• Drive enablement through trainings and maintain knowledge repositories and decision records.
• Implement observability (tracing, metrics, logs), dashboards, and SLO burn and cost anomaly alerting.
• Execute safe releases (canary/shadow/blue/green), and manage versioning, feature flags, and rollback plans.

Skills

enterprise networking

Linux systems

incident troubleshooting

RCA analysis

SLO/SLI frameworks

DR/BCP planning

cloud networking

GPU/AI networking

Education

CCNA

CCNP

Tools

InfiniBand hardware

NVIDIA UFM

Job description

Skill: Network (Enterprise / AI Infrastructure Context)

Skill Requirement

• Strong hands-on expertise in enterprise networking and Linux systems
• Responsible for troubleshooting, performance tuning, and operational stability of network and OS layers supporting AI/HPC/Kubernetes workloads

Networking (L3)

• Certifications (Preferred):
• CCNA (Mandatory baseline)
• CCNP (Strongly preferred)
• Experience:
• 5–10 years in data center / cloud networking operations
• Hands-on experience with:
• Routing & Switching (BGP, OSPF, VLANs)
• Load balancing, firewall basics
• InfiniBand card and switches
• Nvidia UFM
• Skill Depth:
• Strong in incident troubleshooting and RCA
• Ability to diagnose:
• Latency, packet loss, connectivity failures
• Network issues affecting GPU / distributed workloads
• Working knowledge of cloud networking (AWS/Azure/GCP)
• Working Knowledge of AI/HPC networking for distributed training for GPU-GPU communication.
• Define and maintain production readiness standards across platform, data, model, application, and security layers.
• Establish SLO/SLI frameworks for latency, availability, quality, safety, and drift implement error budget policies.
• Maintain compliance mappings (e.g., ISO 27001, SOC 2, GDPR/DPDP, HIPAA where applicable).
• Author PRR checklists, runbooks/playbooks, and DR/BCP blueprints (RTO/RPO, multi‑region/site failover). Drive enablement (trainings, brown-bags) and maintain knowledge repositories and decision records.
• Implement observability (tracing, metrics, logs), dashboards, and SLO burn and cost anomaly alerting.
• Execute safe releases (canary/shadow/blue green), prompt/model versioning, feature flags, and rollback plans.