Summary
What you’ll impact
The Member of Technical Staff, Infrastructure Engineer at the organization will design, scale, and operate the Kubernetes-based platform that powers AI scientist agents. The role involves building infrastructure, tooling, and observability while collaborating with backend, ML, and research teams to ensure reliable, production‑grade environments.
Responsibilities
What you'll do
- Build, maintain, and improve Kubernetes-based infrastructure that supports agent workloads, research services, and internal platforms.
- Contribute to cluster scaling, resource management, and operational improvements as platform usage grows.
- Develop and maintain infrastructure tooling, automation, and deployment workflows that improve reliability and developer productivity.
- Help implement monitoring, observability, and alerting systems to ensure platform health and performance.
- Support storage, networking, and security initiatives within our Kubernetes environments.
- Troubleshoot infrastructure and production issues across distributed systems and participate in incident response efforts.
- Collaborate with backend, ML, and research teams to understand workload requirements and implement reliable infrastructure solutions.
- Contribute to infrastructure best practices, documentation, and operational processes.
Requirements
What you’ll bring
- Typically, 6+ years of software, infrastructure, platform, or DevOps engineering experience.
- Experience working with Kubernetes in development or production environments.
- Familiarity with cloud platforms such as AWS, GCP, or Azure.
- Proficiency in at least one programming language such as Python, Go, Java, or TypeScript.
- Experience with infrastructure-as-code tools such as Terraform, Pulumi, or similar technologies.
- Understanding of containerized applications, networking fundamentals, and distributed systems concepts.
- Experience using CI/CD pipelines, version control systems, and automated testing practices.
- Ability to work independently while collaborating effectively across teams.
- Curiosity, strong problem-solving skills, and a desire to learn new technologies.