Infrastructure Engineer at Ivo AI, Inc.

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Job Title

Infrastructure Engineer

Salary

Not Disclosed

Company Description

Ivo AI, Inc. is a $55M Series B San Francisco startup building AI for legal contracts used by giants like Uber, Shopify, and Reddit.

Job Description

Join Ivo AI, Inc. to build the foundational infrastructure for a high-growth AI platform. You will own multi-cluster Kubernetes deployments across AWS, GCP, and Azure, ensuring high availability and performance for enterprise legal teams. This role involves designing workload isolation strategies, automating environment lifecycle, and translating complex legal requirements into robust technical constraints.

Location

San Francisco, USA

Why this role is remarkable

• Build the multi-cloud backbone for a platform trusted by industry leaders like Uber and Canva, managing complex isolated environments for sensitive legal data.
• High-impact ownership at a well-funded $55M Series B startup, where you will deeply embed with engineering to push the frontiers of LLM infrastructure.
• Work at the intersection of DevOps and cutting-edge AI, designing systems that handle diverse workloads across global regions with sophisticated disaster recovery.

• Own and scale multi-cluster Kubernetes deployments across AWS, GCP, and Azure, implementing failover and disaster recovery strategies that work in real-world scenarios.
• Build internal tooling and infrastructure as code using Pulumi and GitHub Actions to automate environment provisioning, ensuring consistent and secure dev-to-prod pipelines.
• Design and implement security and compliance frameworks, including RBAC and data residency, while optimizing infrastructure for both ML and high-frequency API traffic.

• Has 2+ years of experience deeply managing Kubernetes architecture, including scheduling, networking, and storage primitives, rather than just basic application deployment.
• Expert in Infrastructure as Code using Pulumi or Terraform and CI/CD pipelines, with a proven track record of managing multi-region production environments.
• Possesses a failure-mode mindset with the full-stack range to debug complex distributed systems issues across APIs, workers, and frontend performance builds.

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