AI Infrastructure Engineer

TL;DR

AI Infrastructure Engineer (DevOps/SRE): Building and operating production infrastructure for autonomous AI agents with an accent on observability, controllability, and multi-cloud reliability. Focus on designing infrastructure patterns for non-deterministic systems and hardening IaC stacks across AWS, GCP, and Azure.

Location: New York City

Salary: $180k – $300k

Company

hirify.global transforms critical institutions in healthcare, manufacturing, and energy by deploying frontier applied AI technology.

What you will do

• Define infrastructure patterns for multi-agent AI systems to ensure they are observable, controllable, and recoverable.
• Own and evolve the IaC stack using Terraform and Kubernetes across AWS, GCP, and Azure.
• Build observability primitives to trace agent decisions and execution paths.
• Design and maintain CI/CD pipelines to provide fast and trustworthy feedback loops.
• Establish operational foundations for monitoring, alerting, and incident response for autonomous systems.
• Meet reliability and compliance requirements for regulated environments, including SOC 2 and HIPAA.

Requirements

• 5+ years of experience building and operating production infrastructure in DevOps or SRE roles.
• Strong hands-on experience with Terraform.
• Deep experience with at least one major cloud provider (AWS, GCP, or Azure), covering networking, IAM, and cost management.
• Solid production experience with Docker and Kubernetes.
• Experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, or similar).
• Scripting proficiency in Python, Bash, or similar languages.

Nice to have

• Multi-region and multi-cloud experience across two or more providers.
• Experience with single-tenant or on-prem deployments alongside multi-tenant SaaS.
• Familiarity with GitOps patterns, progressive delivery, and the Grafana stack (Prometheus, Loki).
• Knowledge of compliance frameworks like HIPAA and SOC 2.
• Background supporting the transition of ML or research workflows into production.

Culture & Benefits

• Equity offerings in a fast-growing AI company.
• High-agency environment with real ownership over foundational technical decisions.
• Culture of "Intensity with Kindness," emphasizing candor, excellence, and vulnerability.
• Outcome-oriented work environment without strict 9-5 hour monitoring.
• Opportunity to define new SRE and infrastructure standards for autonomous AI agents.