Enterprise Support Engineer (AI)

Location: Remote in the United States; required to support West Coast business hours and customers.

Salary: $115K–$150K annually, plus equity.

Company

hirify.global provides an AI routing and infrastructure layer for enterprises to access, manage, and optimize large language models across providers.

What you will do

• Own technical resolution for enterprise inquiries and incidents, including code-level debugging and escalation to Engineering.
• Analyze logs, stack traces, API usage, latency, and error patterns to identify issues in customer implementations, hirify.global infrastructure, or upstream model providers.
• Create minimal reproductions with TypeScript, Python, or cURL to confirm defects.
• Assess business impact, support account health with QBR data, and provide latency, token usage, and error-rate analysis.
• Communicate clearly during service disruptions with executive and developer stakeholders.
• Turn investigations into public documentation, internal troubleshooting playbooks, automated remediation tools, and product feedback.

Requirements

• 3–5+ years of experience in an external-facing support role within a B2B SaaS or API-first environment.
• Deep familiarity with REST APIs, HTTP status codes, Server-Sent Events, OAuth, Bearer tokens, Postman, and cURL.
• Ability to read and debug code in at least one customer-facing language such as Python, TypeScript/Node.js, Go, or Java.
• Experience with logging and monitoring platforms such as Datadog, Grafana, Cloudflare logs, or GCP Cloud Logging, plus basic SQL proficiency.
• Knowledge of LLM mechanics, including context windows, tokens, temperature, system prompts, and model providers.
• Experience with high-throughput, low-latency systems, Zendesk or similar tools, and Slack; ability to remain composed during outages and perform systematic, white-box troubleshooting.

Culture & Benefits

• Work at the intersection of Engineering, Support, and Customer Success.
• Use AI and LLMs for debugging, workflow automation, and problem-solving.
• Support enterprise customers relying on critical AI infrastructure.
• Compensation includes equity.