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Design and maintain cloud infrastructure, CI/CD pipelines, and developer tools to support agent research and production deployments. Improve system reliability, scalability, and performance through automation and robust data management workflows.
Join the platform team at an AI/ML company to build the infrastructure and developer tools behind agent research and product deployments. You will help make agent systems reliable, portable, and ready to scale across research and enterprise environments.
Design and maintain cloud infrastructure, storage, CI/CD pipelines, observability, and security for research and production systems.
Build internal developer tools, automation, and shared libraries that help engineering and research teams work efficiently.
Develop reliable workflows for data management, model experimentation, evaluation, and deployment.
Improve build, test, and release processes so prototypes can move smoothly into production.
Monitor system performance, diagnose bottlenecks, and improve the reliability and reproducibility of services and pipelines.
Contribute to platform architecture and scale agent hosting, including availability, security, networking, and cloud portability.
Two to seven years of experience scaling agent infrastructure in platform, infrastructure, or DevOps engineering roles.
Experience deploying and operating agent systems in enterprise environments, with attention to portability across cloud providers.
Strong engineering fundamentals, including concurrency, software architecture, and systems design.
Proficiency with cloud platforms such as AWS or GCP, Docker, Kubernetes, and CI/CD tools such as GitHub Actions and Terraform.
A technical computer science or STEM background, with experience spanning larger organizations and early-stage, product, or research environments.
Familiarity with data pipelines, job scheduling, or ML experimentation workflows, and experience building product infrastructure from the ground up.
Salary range: $200,000 to $300,000 annually. Visa sponsorship is available.
Remote within the United States. Primary location: Palo Alto, California.
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