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Job Description

Insight Global is seeking a Network Engineer to join the Deployment & Integration team supporting large‑scale AI datacenter buildouts. This is a hands‑on, field‑execution role focused on turning up, validating, and scaling hyperscale AI datacenter network infrastructure.

You’ll deploy modern datacenter fabrics at scale—configuring switches, validating physical‑layer connectivity, coordinating with cross‑functional teams, resolving blockers in real time, and ensuring clean, production‑ready handovers to operations.

This role is ideal for engineers who thrive in fast‑paced, high‑growth environments and want deep exposure to hyperscale deployments, large fabrics, and AI/ML cluster turn‑ups. You’ll work closely with senior engineers for technical mentorship and structured onboarding while quickly developing expertise in AI fabric execution. Success in this role means independently owning pod deployments, becoming the go‑to field engineer, and growing into deployment leadership as the organization scales.

Key Responsibilities

Deployment Execution: Deploy and validate datacenter network infrastructure including front‑end and back‑end fabrics, BMS networks, and management networks. Configure switches, install optics, coordinate fiber/cabling work, and drive pods from staging to production readiness.

Physical Layer Validation: Validate insertion loss, perform OTDR tests, troubleshoot optical issues, and ensure all physical connectivity meets production standards. Maintain accurate as‑builts and physical audit documentation.

Hardware Lifecycle Management: Oversee hardware logistics including staging, rack/stack coordination, RMAs, and inventory tracking for hyperscale deployments.

Cross‑Functional Coordination: Partner with DC Operations, ICT teams, Hardware Engineering, and Network Engineering to keep build milestones on track.

Documentation & Process Improvement: Contribute to deployment playbooks, SOPs, and repeatable operational processes.

Operational Support: Provide backup operational support during and after deployments, including incident response, break/fix, and troubleshooting across physical and logical layers.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

3–7 years of network engineering experience including direct hands‑on work in hyperscale datacenter environments (AI/ML clusters, large fabrics, multi‑site deployments, or cloud‑scale DCs).

Strong understanding of modern datacenter fabrics (EVPN/VXLAN, BGP, CLOS architectures).

Hands‑on experience configuring production network infrastructure and troubleshooting across physical and logical layers.

Ability to interpret OTDR traces, validate insertion loss, and debug optical and BGP issues.

Excellent coordination and communication skills for cross‑team collaboration in high‑volume build environments.

Comfortable with 70–80% travel for onsite deployment support. Experience in AI/ML networking (RoCEv2, PFC, ECN).

Exposure to vendor platforms such as Arista, Juniper, and NVIDIA.

Strong understanding of structured cabling standards and fiber optics.

Familiarity with automation concepts and scripting (Python, Ansible).

Experience with DCIM tools, asset management systems, and deployment management workflows.