Infrastructure Platform Engineer (AI)

Location: Palo Alto, United States; work arrangement: on-site

Company

hirify.global Intelligence is a frontier AI lab building self-improving systems for chip design and accelerating AI-driven hardware development.

What you will do

• Design, build, and extend a self-managed cloud platform using Terraform and establish reusable infrastructure-as-code patterns.
• Own platform deployments across multiple environments, including performance, security, reliability, and scalability.
• Design, implement, and operate production CI/CD pipelines in GitHub Actions for mission-critical repositories.
• Architect scalable AI tooling and developer-experience workflows across distinct user environments in collaboration with physical-design engineers.
• Build an observability stack covering pipeline health, application metrics, and ML workloads.

Requirements

• BS in computer science, computer engineering, electrical engineering, or a related field, or equivalent practical experience.
• 4+ years of hands-on infrastructure or platform engineering experience owning systems used by others.
• Production ownership of infrastructure-as-code architecture, including maintenance and new features.
• Experience designing and implementing production CI/CD pipelines that build and ship reproducible artifacts with attention to performance, scalability, and security.
• Experience with observability tooling for pipeline health and application-level metrics.

Nice to have

• Hands-on experience with GCP, Kubernetes, and GitHub Actions, including custom runners.
• Experience running ML training and evaluation infrastructure with GPU or TPU compute.
• Familiarity with LLM observability, including tracing, evaluations, and cost and latency monitoring.
• Security experience with supply-chain hardening, OIDC authentication, least-privilege secrets, SOC 2, or penetration testing.
• Early-stage startup experience building infrastructure from zero or near-zero.

Culture & Benefits

• Fast-paced frontier AI research environment.
• Direct impact on infrastructure supporting chip-design and AI workloads.
• Work alongside researchers and engineers with experience from leading AI, semiconductor, academic, and technology organizations.
• Backed by $335M from Sequoia, Lightspeed, DST, and NVIDIA Ventures.