Software Engineer (AI Infrastructure)

Location: Hybrid, US and Canada offices

Company

AI hardware and software company building large-scale systems for high-speed AI training and inference.

What you will do

• Design, build, and maintain CI/CD systems for build, testing, integration, qualification, and release workflows.
• Build and operate Kubernetes-based platforms and services for engineering teams.
• Develop deployment systems, internal tools, and self-service workflows that make infrastructure changes repeatable and safe.
• Improve infrastructure reliability, capacity, performance, cost efficiency, monitoring, and operational readiness.
• Debug failures across CI pipelines, Kubernetes, networking, storage, authentication, operating systems, and distributed applications.
• Perform root-cause analysis and partner with software, IT, security, networking, release, and developer-productivity teams on scalable infrastructure solutions.

Requirements

• 5+ years of professional experience in platform engineering, DevOps, infrastructure engineering, site reliability engineering, or software engineering.
• Hands-on experience with CI/CD pipelines, automated software delivery, Kubernetes, and containerized environments.
• Experience with a major cloud platform, preferably AWS, and programmatic infrastructure provisioning.
• Strong Linux or Unix fundamentals and understanding of DNS, routing, load balancing, proxies, ports, TLS, and service connectivity.
• Proficiency in Python, Shell, or another language used for infrastructure automation and operational tooling.
• Experience with monitoring, logging, alerting, dashboards, incident investigation, and cross-system debugging.

Nice to have

• Experience with Terraform, Kubernetes controllers or operators, custom resources, Helm, Argo CD, or similar platform technologies.
• Experience managing artifact repositories, package registries, build caches, or software-distribution infrastructure.
• Familiarity with build systems, dependency management, reproducible builds, and internal developer platforms.
• Experience supporting hybrid cloud, on-premises, and specialized-hardware environments.
• Experience with identity and access management, secrets, certificates, TLS, or mTLS; a BS/MS in Computer Science or equivalent practical experience.

Culture & Benefits

• Work on an AI platform designed to go beyond GPU limitations.
• Contribute to cutting-edge AI research and open-source projects.
• Work with one of the fastest AI supercomputers in the world.
• Combine startup vitality with job stability and a non-corporate work culture.
• Work in an inclusive environment focused on continuous learning, growth, and support.