обновлено 5 дней назад
AI Infrastructure Engineer
180 000 - 400 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Infrastructure Engineer (AI/Cloud Infrastructure): Building and operating the infrastructure, deployment systems, and reliability foundations for autonomous AI agents with an accent on multi-cloud infrastructure, observability, and production operations. Focus on defining infrastructure patterns for agentic systems, tracing agent decisions, and hardening Terraform, Kubernetes, and CI/CD across regulated environments.
Location: New York City, on-site
Salary: $180K–$400K annually, plus equity
Company
applies frontier AI to transform critical institutions in healthcare, manufacturing, energy, and other regulated industries.
What you will do
- Define infrastructure patterns for observable, controllable, and recoverable multi-agent AI systems.
- Own and evolve Terraform and Kubernetes infrastructure across AWS, GCP, and Azure.
- Build observability primitives that trace agent decisions and execution paths.
- Design and maintain CI/CD pipelines from commit through production.
- Build operational foundations for monitoring, alerting, incident response, and reliability.
- Work with engineering teams on reliability and compliance requirements for regulated customers.
Requirements
- 5+ years of experience building and operating production infrastructure in DevOps or SRE roles.
- Strong hands-on Terraform experience and deep expertise with at least one major cloud provider.
- Production experience with Docker and Kubernetes, including managed clusters.
- Experience designing and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, or similar tools.
- Proficiency in Python, Bash, or a similar scripting language.
- High agency, strong communication, and genuine curiosity about AI systems and autonomous decision-making.
Nice to have
- Multi-region and multi-cloud experience across two or more providers.
- Experience with single-tenant, on-premises, and multi-tenant SaaS deployments.
- Familiarity with GitOps, progressive delivery, and the Grafana stack.
- Experience with HIPAA, SOC 2, and other compliance requirements in regulated environments.
- Experience moving ML or research workflows into production.
Culture & Benefits
- Small team with substantial ownership of foundational technical decisions.
- Work focused on ambitious AI infrastructure problems that are still being defined.
- Culture emphasizes customer outcomes, high-agency decision-making, direct communication, and collaboration.
- Work is not limited to fixed 9-to-5 hours, with an emphasis on meaningful outcomes rather than monitored hours.
- Compensation includes equity.
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