About the Role
This is a hands-on infrastructure engineering role at an early-stage enterprise AI company building a context and data governance layer for AI agents in highly regulated industries. You will own the inference and model-serving infrastructure end to end, ensuring AI agents run reliably, accurately, and at scale in production environments where performance is non-negotiable.
What You'll Do
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Design, build, and operate inference and model-serving infrastructure from development through production deployment.
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Scale systems to support AI agents running reliably under increasing concurrency and production load.
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Identify and resolve infrastructure bottlenecks in close collaboration with ML and platform engineering teams.
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Optimize systems for latency, throughput, and reliability at scale.
What We're Looking For
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5 or more years building and operating machine learning inference systems, model-serving platforms, or ML infrastructure in production environments.
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Hands-on experience designing and scaling inference serving infrastructure using tools such as TensorFlow Serving, TorchServe, Triton, KServe, or equivalent custom systems.
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Strong systems engineering fundamentals with expertise in distributed systems, containerization, and orchestration (Docker, Kubernetes).
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Demonstrated ability to optimize production ML systems for latency, throughput, and reliability under high concurrency.
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Experience with cloud infrastructure platforms such as AWS, GCP, or Azure for deploying and managing ML workloads.
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Proficiency with monitoring, observability, and debugging tools such as Prometheus, Grafana, ELK, or distributed tracing frameworks.
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Proficiency in at least one systems programming or backend language: Python, Go, Rust, C++, or Java.
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Experience with knowledge graphs, semantic search, or graph databases (e.g., Neo4j, Amazon Neptune) is a plus.
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Familiarity with agentic AI systems, autonomous agents, or multi-step reasoning pipelines is a plus.
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Experience with enterprise data infrastructure, data pipelines, or data integration platforms is a plus.
Location
This role is on-site in San Mateo, California. Visa sponsorship is not available.
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