Solutions Architect

Insight • Fort Worth, TX

5d • $70,000 - $85,000 • Hybrid

About The Position

Now is the time to bring your expertise to Insight. We are not just a tech company; we are a people-first company. We believe that by unlocking the power of people and technology, we can accelerate transformation and achieve extraordinary results. As a Fortune 500 Solutions Integrator with deep expertise in cloud, data, AI, cybersecurity, and intelligent edge, we guide organizations through complex digital decisions. We’re looking for an early-career engineer who wants to get their hands on real, complex infrastructure — on-prem AI compute and hybrid cloud across all three major Hyperscalers — in an R&D setting where experimentation is encouraged and learning is built into the work. You’ll grow alongside experienced engineers and build toward a Senior Architect track over time. If you run a home lab, have broken something on a weekend just to understand why, or get genuinely excited about new hardware and infrastructure tech — this role was written for you.

Requirements

• Bachelor’s degree in CS, IT, or related field — or equivalent experience that shows you know your stuff.
• Genuine curiosity about infrastructure, AI systems, and how things work at a low level.
• Strong troubleshooting instincts and a “I’ll figure it out” mindset.
• Clear communicator — comfortable talking to both internal teammates and partners
• Hands-on experience with Windows and/or Linux/Unix — even on your own hardware.
• Networking fundamentals: TCP/IP, VLANs, subnetting.
• Scripting in Python, Bash, or PowerShell.
• GPU hardware familiarity or exposure to AI/ML compute infrastructure.
• Virtualization platforms: Hyper-V, Nutanix, Proxmox, & Red Hat OpenShift
• Physical infrastructure knowledge (not exhaustive): Lenovo, Dell, Cisco, HPE, NetApp & Everpure
• Infrastructure-as-code: Ansible, Docker, or Kubernetes.

Responsibilities

• Support and maintain on-prem GPU cluster infrastructure used for AI training, inference, and R&D workloads.
• Work hands-on with all three major cloud hyperscalers (AWS, Azure, GCP), including AI/ML services and experimental deployments.
• Use AI developer tools (GitHub Copilot, Claude Code, Google Gemini) as part of your everyday workflow.
• Build, rack, cable, and configure servers, GPU hardware, network switches, and storage devices in a lab environment.
• Support POC and testing environments — standing things up, validating them, and tearing them down as needed.
• Monitor system performance, troubleshoot hardware and software issues, and perform routine maintenance.
• Assist with system administration: user management, software deployment, and basic network configuration.
• Participate in infrastructure automation efforts including Ansible playbook execution and containerization.
• Document lab processes and procedures, and infrastructure configurations.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Associate degree