Infrastructure Engineer (AI)

Location: San Francisco, United States; on-site

Company

hirify.global develops general-purpose AI, foundation models, and learning algorithms for robots and physically actuated devices.

What you will do

• Operate and scale Kubernetes clusters and service deployment patterns for AI-native internal infrastructure.
• Build scalable microservice platforms for evaluation services, operational tooling, and internal APIs.
• Design security, authentication, authorization, networking, observability, alerting, and cost-visibility systems.
• Develop multi-cloud infrastructure foundations, quota and rate-limiting services, and standardized platform abstractions.
• Improve local and remote development workflows and self-service infrastructure usage.
• Partner with researchers and engineers to own infrastructure systems from design through operation.

Requirements

• Deep experience with GCP, AWS, distributed systems, compute orchestration, networking, autoscaling, service meshes, and load balancing.
• Strong Kubernetes experience, including cluster reliability and service-oriented architectures.
• Experience with Terraform or similar infrastructure-as-code tools, containerization, and platform engineering practices.
• Experience with logging, metrics, tracing, incident response, SLOs, and debugging complex distributed systems.
• Strong understanding of scalability, performance tuning, failure modes, and infrastructure cost optimization.
• 4–6 years of experience in fast-moving or early-stage environments, with strong ownership and cross-functional communication.

Nice to have

• Experience with large-scale machine learning training, evaluation, or simulation infrastructure.
• Experience with secrets management systems such as Doppler.
• Background in observability, cost optimization, internal platform tooling, robotics, simulation, or real-time systems.

Culture & Benefits

• Work alongside engineers, scientists, roboticists, researchers, and platform specialists.
• Own systems end-to-end in an environment where ambiguity and rapidly changing requirements are expected.
• Contribute to infrastructure supporting foundation models and fleets of physical robots.