Software Field Applications Engineer (AI Infrastructure)

Location: Hybrid work from the Palo Alto headquarters, with travel to customer sites and industry events typically 25–40%.

Salary: $140,000–$180,000 per year plus equity, benefits, and 401(k).

Company

hirify.global is a stealth-mode startup building software to improve performance, scalability, and resiliency in large-scale AI data center clusters.

What you will do

• Lead technical discovery, solution design, demonstrations, RFP/RFI responses, and competitive evaluations for AI infrastructure software.
• Own proof-of-concept, early-access, pilot, and production deployments from scoping through production conversion.
• Provide hands-on post-sales support, including integration, troubleshooting, performance tuning, upgrades, cluster expansion, and escalation management.
• Build technical relationships with infrastructure, SRE, and platform engineering teams at hyperscalers, neoclouds, and AI labs.
• Create runbooks, integration guides, reference architectures, demo environments, and technical sales collateral.
• Channel customer feedback, product gaps, bugs, and competitive intelligence to product and engineering teams.

Requirements

• 5+ years of experience in a customer-facing technical role such as FAE, sales engineer, solutions architect, or TAM for infrastructure software.
• Experience supporting or selling AI infrastructure software involving orchestration, telemetry, analytics, or infrastructure management platforms.
• Direct experience working with hyperscalers, neoclouds, or AI labs and understanding their procurement processes and operational scale.
• Strong knowledge of GPU/XPU clusters, high-speed interconnects including InfiniBand, RoCE, Ethernet, and NVLink, job scheduling, and inference or training workloads.
• Hands-on proficiency with Linux, containers, APIs, Python, and Bash for demonstrations, integrations, and troubleshooting.
• Strong communication skills and willingness to travel to customer sites and industry events as needed.

Nice to have

• Experience taking early-stage or pre-launch products into hyperscale accounts.
• Familiarity with inference serving, KV-cache behavior, disaggregated serving, and GPU utilization analysis.
• Experience with Prometheus, Grafana, OpenTelemetry, and infrastructure analytics data pipelines.
• Background at an AI infrastructure software vendor, GPU cloud provider, networking vendor, or hyperscaler.

Culture & Benefits

• Ownership, trust, integrity, respect, and shared responsibility.
• Direct access to engineering leadership and a fast feedback loop from field to product.
• Influence over how the software is sold, deployed, and supported.
• Meaningful early-stage equity and competitive compensation.
• Comprehensive health, dental, and vision coverage plus retirement benefits.

Hiring process

• Submit a resume and a brief note describing a hyperscaler, neocloud, or AI lab engagement led, including the technical challenges and outcome.