> Markdown version of [/jobs/ext/2610629-compute-engineer-deployment](https://www.wearedevelopers.com/jobs/ext/2610629-compute-engineer-deployment). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Compute Engineer, Deployment - **Company:** Insight Global - **Location:** Middletown, DE, United States - **Contract:** Permanent contract - **Skills:** Intelligent Platform Management Interface, BIOS, Data Centers, Data Center Infrastructure Management (CIM), Linux, Firmware, Python (Programming Language), Kubernetes, Bare Metal - **Published:** August 7, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3343333951&tx=JP2721FFG&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role This person has: brought up server or GPU fleets at scale, hundreds of nodes or more, and taken them all the way to production. Worked deep within Linux and out-of-band management: BMC, IPMI, and Redfish are daily tools for you, not occasional lookups. Has automated hardware workflows in Python or Go rather than clicking through them, and the second time you do anything by hand you turn it into software. Has worked physically in data halls, racking, cabling, and swapping components, and you're just as effective acting as remote hands or directing them. Be able to triage failures methodically across hardware, firmware, and software, isolating the fault to a component before reaching for a fix. Willing to travel for turn-up windows when a new data hall comes online. Bonus: Kubernetes-based bare-metal provisioning. Accelerator platform bring up (NVIDIA, AMD, or custom). Burn-in and stress harness design. DCIM and inventory tooling. ## Description This Compute Engineer will bring gigawatts of accelerators from first power-on to production. Facility availability to ready-for-service across thousands of racks per site, with a new data hall landing every few weeks. They will make rack qualification faster than the fleet grows. Firmware baselines, burn-in, and cluster validation proven on every rack before a customer workload touches it, at a pace that never becomes the critical path. They must be able to scale by tooling, not headcount. Deployed megawatts grow severalfold next year while the team stays near-flat, because anything done twice by hand becomes software. Must own compute turn-up from facility availability to ready-for-service: the stretch after the network hands off and before customers run workloads. Ability to qualify racks at scale: establish firmware baselines, configure BMC and BIOS, run burn-in, and validate at node and cluster level across hundreds of racks per site on GPU and custom accelerator platforms. Drive qualification through the base-management Kubernetes platform and provisioning stack (discovery, imaging, firmware updates, shared services), burning down qual queues with tooling rather than manual runs. Triage hardware failures found in qualification: isolate to component, drive RMA and vendor escalation, and feed failure patterns back into the qual gates. Run turn-up remotely by default, with on-site pulses of roughly a week per data hall as new halls reach facility availability, plus occasional overlapping-site weeks. Partner with network deployment, ICT, data center operations, and hardware teams during turn-up windows, and support incident response on freshly-live capacity. 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