U

Upscale AI

High-performance AI networking hardware and software

Forward-Deployed Engineer - AI Fabric, Data Center Switching / SONiC

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA$180k - $285k /yr

About the Job

Requirements

  • At least 8 years of customer-facing escalation, field, or site reliability engineering experience 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, including Kubernetes and Docker, and CI/CD tools such as GitLab or Jenkins.
  • Experience with infrastructure as code and automation using Terraform, Python, and Bash, and comfort using AI coding assistants.
  • Strong Linux troubleshooting skills across host, network stack, and application layers, including RHEL, Ubuntu, and CentOS.
  • Multi-cloud and virtualization experience with GCP, AWS, Azure, OCI, VMware ESXi/vSphere, KVM, and Hyper-V.
  • Working networking and security knowledge, including IP routing basics, VPC design, VPN, firewalls, security groups, TLS, and WAF.
  • Experience with monitoring and observability using Prometheus and Grafana, including alerting for high-availability services.
  • Tier 2 or escalation experience driving customer incidents to resolution across SRE, engineering, and product.
  • Customer-facing communication skills, including technical documentation such as deployment guides, runbooks, and test plans.
  • Follow through on issues until the root cause is confirmed and the fix is verified.

Responsibilities

  • 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 switching specialists; isolate issues across host, Linux, container, virtualization, cloud, and security layers, and distinguish fabric problems from host and workload problems.
  • Integrate company systems with customer cloud, automation, observability, and security tooling.
  • Report recurring field issues and product recommendations to product and engineering.
  • Scope and deliver Professional Services engagements covering deployment, integration, automation, health checks, performance validation, and upgrades.
  • Plan and run customer User Acceptance Testing (UAT), including test plans, execution, issue tracking, and sign-off.
  • Produce engagement deliverables, including design and deployment documents, runbooks, and as-built documentation.
  • Build the Professional Services practice with team and sales leadership by developing service offerings, delivery standards, templates, and playbooks.
  • Run knowledge transfer and training for customer teams at handoff.
  • 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.
  • Build runbooks from case feedback and proactive work, and turn them into automation and training data for the AI monitoring agent with its lead developer.
  • Build Prometheus and Grafana dashboards and alerts connecting switch, host, and NIC telemetry.
  • Read Python, Go, and C source code and NOS-side scripts to confirm root cause.
  • Serve as a technical resource for field engineers, sales engineers, and other customer-facing teams.
  • Support pre-sales technical discussions and proofs of concept.
  • Participate in an on-call rotation and travel to customer sites.

Desired Qualifications

  • Professional Services delivery experience, including scoping, statements of work, and customer acceptance.
  • Pre-sales, proof-of-concept, or customer UAT experience.
  • Data center switching experience with Ethernet, BGP, QoS (PFC and ECN), and optics.
  • Experience with SONiC, RoCEv2, NCCL, or GPU cluster networking.
  • Experience with AI or ML tooling, or building datasets for ML classification.
  • Experience with NVIDIA networking hardware (Spectrum, ConnectX, BlueField) or Ultra Ethernet.
  • Experience with traffic generation and test tools such as Keysight/Ixia.
  • Penetration testing and security hardening experience, for example with Qualys.
  • Experience leading small teams or technical workstreams.

About the Company

Upscale AI

High-performance AI networking hardware and software

Upscale AI builds a full-stack, high-performance AI networking platform to scale up GPU compute. It designs purpose-built silicon chips and a software orchestration layer that connects thousands of GPUs into a single, unified compute engine. The system is optimized for the heavy data movement and bursty traffic of large language model training and inference, enabling fast, scalable AI workloads. Unlike traditional, vendor-driven networking stacks, Upscale AI offers open-standard networking powered by silicon and software, and participates in consortia like UEC and SONiC to ensure interoperability across different hardware environments. Its customers include global hyperscalers, AI-first enterprises, and sovereign cloud providers who need large-scale, interoperable AI clusters without lock-in. The company’s goal is to democratize AI infrastructure by delivering high-performance, open-standard solutions that let organizations build and operate massive AI clusters more efficiently.

Company size
201-500
Company stage
Series A
Total funding
$490M
Headquarters
Santa Clara, CA
Founded
2024

Recently Posted Jobs

Explore more opportunities at Upscale AI

See more jobs