Forward-Deployed Engineer, AI Fabric

Job Description

Job DescriptionWhy join Upscale, Inc.

Upscale, Inc., is building the high-performance infrastructure powering the next generation of artificial intelligence. Backed by over $500M in funding and rapid global adoption, we are scaling systems designed for the world’s most demanding AI workloads.

We focus on first-principles engineering across silicon, systems, and networking—where performance, scale, and execution are critical. Our team is talent-dense and high-performing. We value ownership, technical rigor, and speed, and we offer the opportunity to work on foundational problems with immediate, real-world impact.

If you’re looking to do high-impact work, move fast, and help define the infrastructure behind the future of AI—Upscale is where you can produce meaningful work at the frontier—and operate at a high standard.

Role Scope and Impact:

We are hiring a Forward-Deployed Engineer focused on lab, runbook automation, and Professional Services work. You will deploy, validate, and stabilize customer AI fabric environments at customer sites and from our office. You will build the lab environments that reproduce and resolve field issues, write the runbooks that drive our AI monitoring agent, and deliver Professional Services engagements from scoping through handoff. You will work closely with engineering, product, and sales, and build fabric-level triage skills alongside our switching specialists.

This role delivers results in five areas:

• Forward-deployed engineering. Hands-on work with customers through deployment, bring-up, and escalations, shortening the time to a stable production fabric.

• Professional Services. Scoped, repeatable services, including deployment, integration, health checks, upgrades, and User Acceptance Testing (UAT), delivered to a consistent standard as a core team function.

• Lab validation. Customer-representative lab environments for issue reproduction, fix validation, UAT dry runs, and proofs of concept.

• Runbooks and automation. Runbooks built from case feedback and proactive work that drive the automation in our AI monitoring agent.

• Enablement. Technical guidance and documentation for field and sales teams.

Responsibilities:

Forward-Deployed Engineering

• Work directly with customer platform and operations teams through deployment, bring-up, cutover, and upgrades.

• Drive customer escalations to a verified fix with engineering and our switching specialists. Isolate issues across host, Linux, container, virtualization, cloud, and security layers, and separate fabric problems from host and workload problems.

• Integrate Upscale systems with customer cloud, automation, observability, and security tooling.

• Report repeat field issues and product recommendations to product and engineering.

Professional Services:

• Scope and deliver Professional Services engagements: deployment, integration, automation, health checks, performance validation, and upgrades.

• Plan and run User Acceptance Testing (UAT) with customers: test plans, execution, issue tracking, and sign-off.

• Produce engagement deliverables: design and deployment documents, runbooks, and as-built documentation.

• Build out the team's Professional Services practice with team and sales leadership: service offerings, delivery standards, templates, and playbooks.

• Run knowledge transfer and training for customer teams at handoff.

Lab:

• Design and build customer-representative lab topologies for issue reproduction, fix validation, and proofs of concept.

• Run pre-deployment validation and UAT dry runs before customer sign-off.

• Automate test setup, test runs, and data capture with Python, Bash, and Terraform.

• Reproduce and qualify issues before they reach development.

• Define lab environment requirements and coordinate them with IT.

Runbooks and Automation:

• Build runbooks from case feedback and proactive work, and turn them into automation and training data for our AI monitoring agent with the agent's lead developer.

• Build Prometheus and Grafana dashboards and alerts that tie switch, host, and NIC telemetry together.

• Read source code (Python, Go, C) and NOS-side scripts to confirm root cause.

Enablement:

• Serve as a technical resource for field engineers, sales engineers, and other customer-facing teams.

• Support pre-sales technical discussions and proofs of concept.

Requirements:

• 8+ years in customer-facing escalation, field, or site reliability engineering at a networking or security vendor.

• Experience deploying and supporting products in customer environments across private cloud, public cloud, and virtualized platforms.

• Hands-on experience with production container platforms: Kubernetes, Docker, and CI/CD (GitLab, Jenkins).

• Infrastructure as code and automation with Terraform, Python, and Bash. Comfortable using AI coding assistants to move faster.

• Strong Linux (RHEL, Ubuntu, CentOS) troubleshooting across host, network stack, and application layers.

• Multi-cloud and virtualization depth: GCP, AWS, Azure, OCI, plus VMware ESXi/vSphere, KVM, and Hyper-V.