Field Service Delivery Engineer - AI Infrastructure

SHI International Corp.•Piscataway, NJ

1d•$90,000 - $150,000•Onsite

About The Position

The Service Delivery Engineer – AI Infrastructure is a senior, hands on engineering role within SHI’s Integration Data Center Solutions (IDCS) team. This position focuses on the deployment, integration, and validation of enterprise grade AI infrastructure—including NVIDIA Base Pods and OEM systems from Dell, HPE, and Lenovo—across both the SHI Data Center Factory and customer data centers. This engineer will work directly with servers, storage, networking, Kubernetes clusters, and NVIDIA AI systems, ensuring that racks are fully integrated, burned in, configured, and ready for production. The role requires deep experience with enterprise hardware, Linux systems, Python, and data center networking, combined with strong customer facing communication and the ability to operate independently in dynamic environments. When not traveling for onsite deployments, the engineer will report to the SHI Data Center Factory in Piscataway, NJ.

Requirements

A bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
5+ years’ experience with enterprise data center hardware (servers, storage, networking)
Strong Linux administration (install, configure, troubleshoot)
Proficient in Python scripting for automation and system validation
In-depth knowledge of L2/L3 networking, VLANs, routing, switches, and cabling
Experience with firmware/BIOS updates, device drivers, and system bring-up
Hands-on experience deploying Kubernetes or containerized environments
Familiarity with NVIDIA GPU systems, orchestration tools (e.g., Base Command Manager)
Excellent written and verbal communication skills for customer interactions
Self-driven, proactive, and able to work independently
Quick learner, able to adapt to evolving AI infrastructure technologies
Ability to lift/move up to 50 lbs and work in data center environments
Ability to travel and work flexible hours, including weekends, as needed
The ability to write, debug, and maintain code in programming languages such as Python, R, or Java to support AI initiatives – Intermediate
The ability to effectively utilize applications like Word, Excel, PowerPoint, and Outlook to enhance productivity and perform various tasks efficiently. - Intermediate
Ability to simplify and effectively communicate complex problems to stakeholders across various functions and levels. - Intermediate
Expertise in installing, maintaining, and troubleshooting BIOS firmware and device drivers to ensure system functionality and performance. - Intermediate
Understanding of deploying and managing mobile devices to ensure seamless operation and integration within an organization preferred - Intermediate
Experience with installing, configuring, and maintaining Linux-based operating systems preferred - Intermediate

Nice To Haves

Experience deploying AI or HPC infrastructure in enterprise environments.
Strong understanding of data center networking and security best practices.
Experience with OEM enterprise hardware (Dell, HPE, Lenovo, Supermicro).
Certifications such as Linux+, CCNA/CCNP, NVIDIA certifications, or data center‑focused credentials.
Experience working with diverse teams and adapting to different customer cultures and environments.

Responsibilities

Lead the end to end deployment of AI infrastructure, including rack/stack, cabling validation, system bring up, firmware updates, burn in, and cluster configuration.
Integrate and validate NVIDIA Base Pods and OEM AI systems, including Base Command Manager, Kubernetes installation, and GPU node readiness.
Perform advanced system engineering tasks, such as BIOS/firmware updates, redundancy testing, stress testing, and network configuration.
Collaborate with SHI build technicians to ensure factory level integration is complete before systems ship to customer sites.
Stand up and validate systems onsite at customer data centers, ensuring seamless handoff into their environment.
Troubleshoot complex hardware, Linux, and networking issues across compute, storage, and switching layers.
Document configurations, runbooks, and deployment steps, contributing to repeatable and scalable delivery processes.
Engage directly with customers, providing clear communication, technical guidance, and a professional onsite presence.
Manage priorities and timelines independently, especially during onsite deployments where ambiguity and rapid problem solving are common.
Travel as needed to customer locations for hands on deployment and integration work.