About the Role
Join an AI product team building the platform that supports customer-facing agent applications. You will work across backend infrastructure, developer tooling, and MLOps to help research and product teams develop, deploy, and operate reliable systems.
What You'll Do
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Build and maintain cloud infrastructure for compute, storage, CI/CD, observability, and security.
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Develop internal tools, automation, and shared libraries that improve engineering productivity.
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Create reliable systems for data management, model experimentation, evaluation, and deployment.
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Improve build, test, and release workflows from research prototypes through production.
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Monitor service and pipeline performance, diagnose bottlenecks, and improve reliability and reproducibility.
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Design backend services for agent hosting, availability, tracking, security, networking, and scaling.
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Contribute to platform architecture and infrastructure strategy as the product grows.
What We're Looking For
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Five to twelve years of backend or platform engineering experience, including senior or staff-level individual-contributor work and daily coding.
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Experience building a backend platform from scratch for an external product, ideally involving LLMs or agents.
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Recent hands-on experience with production LLM or agent systems, such as serving, orchestration, tool use, memory, or evaluation.
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Strong backend fundamentals in Python or Go, APIs, databases and storage, and distributed systems.
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Working experience with Kubernetes and a major cloud provider, such as AWS or Google Cloud.
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Experience spanning both larger technology organizations and startups or research environments, with broad ownership of a system.
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Familiarity with data pipelines, job scheduling, or ML experimentation workflows.
Compensation & Benefits
Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is available.
Location
On-site in Palo Alto, California, United States.
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