Senior Post-Sales Customer Engineer (AI)

TL;DR

Senior Post-Sales Customer Engineer (AI): Ensure smooth deployment, performance, and reliability of ML workloads in production for strategic customers with an accent on Kubernetes troubleshooting, infrastructure debugging, and incident management. Focus on diagnosing runtime issues, managing escalations, and driving product improvements through customer feedback.

Company

hirify.global powers inference for leading AI companies by uniting applied AI research, flexible infrastructure, and developer tooling, backed by $150M Series D funding.

What you will do

• Diagnose and resolve runtime issues related to latency, memory, GPU utilization, concurrency, and model lifecycle management.
• Debug infrastructure issues across Kubernetes, networking, observability, and alerting systems.
• Lead incident response during outages or escalations, coordinating between multiple teams.
• Serve as technical owner for top enterprise accounts with strict SLAs and responsiveness expectations.
• Translate user feedback into product improvements, runbooks, and best practices.
• Manage projects end-to-end including scoping, execution, and stakeholder communication.

Requirements

• 3+ years experience in fast-paced, customer-facing engineering roles
• Deep Kubernetes troubleshooting expertise and infrastructure debugging skills
• Experience managing high-severity incidents with major customers and SLAs
• Strong project management and organizational skills with ownership mindset
• Excellent communication skills and executive presence during escalations

Nice to have

• Experience with high-performance AI models and ML pipelines
• Familiarity with ticketing and incident-response systems like Zendesk or Pylon
• Knowledge of Helm, Flux, CI/CD tooling, or scripting automations

Culture & Benefits

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