Customer Engineer (AI)

TL;DR

Customer Engineer (AI): Owning the post-sales technical relationship with strategic and enterprise customers, ensuring their AI models are healthy and their roadmap is heard with an accent on infrastructure debugging, AI/ML performance, and incident command. Focus on resolving issues across Kubernetes, GPUs, networking, and model serving, and translating pain points into product improvements.

Location: San Francisco, New York, or Remote within the United States

Salary: $165K – $330K

Company

hirify.global powers mission-critical inference for dynamic AI companies by uniting applied AI research, flexible infrastructure, and seamless developer tooling.

What you will do

• Serve as the first responder to post-sales customer issues, triaging and resolving Tier 1 and Tier 2 issues.
• Diagnose runtime issues related to latency, memory behavior, GPU utilization, concurrency, and model lifecycle management.
• Lead incident response during outages and escalations, coordinating across Product, SRE, Sales, and Engineering.
• Own customer communication through resolution, including delivering root-cause analyses.
• Set up and maintain proactive monitoring and alerts for all customer production models.
• Translate user feedback into roadmap signals, documentation improvements, and product enhancements.

Requirements

• Deep Kubernetes troubleshooting expertise, including resource debugging, pod/runtime analysis, and log-based diagnostics with observability tooling (Grafana, Loki, Prometheus).
• Strong infrastructure debugging across container orchestration, networking, and service dependencies, with hands-on production cluster experience.
• Experience managing high-severity incidents with major customers, including SLAs, war rooms, and post-incident reviews.
• Proven project management skills with an ownership mindset.
• Ability to translate recurring technical pain points into roadmap-level insights and product improvements.
• Strong communication skills and executive presence during high-visibility situations.
• 3+ years of experience in a fast-paced, high-growth, or customer-facing engineering environment.

Nice to have

• Familiarity with high-performance AI model serving, including troubleshooting ML pipelines from preprocessing through inference.
• Experience with ticketing and incident-response platforms such as Pylon or Zendesk.
• Hands-on experience with Helm, Flux, CI/CD tooling, or scripting automations for deployment and operational workflows.
• Background in SRE, DevOps, or forward-deployed engineering roles at an infrastructure company.

Culture & Benefits

• Competitive compensation, including meaningful equity.
• 100% coverage of medical, dental, and vision insurance for employee and dependents.
• Generous PTO policy including company wide Winter Break.
• Paid parental leave.
• Company-facilitated 401(k).
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.