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This is a founding infrastructure role at an early-stage AI infrastructure startup building an enterprise context layer for AI agents. You will design and build the cloud infrastructure from scratch, owning every architectural decision that shapes how the platform scales and operates for years to come.
This is a founding infrastructure role at an early-stage AI infrastructure startup building an enterprise context layer for AI agents. You will design and build the cloud infrastructure from scratch, owning every architectural decision that shapes how the platform scales and operates for years to come.
Design and build cloud infrastructure from the ground up to power a semantic, AI-focused enterprise platform.
Own the full lifecycle of infrastructure, from initial architecture through production deployment and scaling.
Establish foundational best practices, standards, and tooling where none currently exist.
Build and maintain CI/CD pipelines and deployment automation systems.
Architect and manage Kubernetes clusters and container orchestration in production.
Implement infrastructure monitoring, observability, and logging systems.
Design and operate database infrastructure spanning relational and NoSQL systems at scale.
Implement infrastructure security, networking, and access control solutions.
5 to 12 years of hands-on experience building and operating cloud infrastructure in production environments.
Strong experience with at least one major cloud platform: AWS, GCP, or Azure, including networking, storage, compute, and managed services.
Proven experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi.
Production experience architecting and managing Kubernetes clusters or equivalent container orchestration platforms.
Comfort operating at startup pace, building from scratch rather than maintaining or extending established systems.
Stable employment history with a track record of end-to-end infrastructure ownership.
Experience building data pipelines or data infrastructure is a plus.
Familiarity with knowledge graphs, semantic systems, or graph databases is a plus.
Experience with machine learning or AI/ML platform infrastructure is a plus.
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