GenAI Infra Engineer: Kubernetes, AWS & IaC Expert

Obsidian; San Francisco (CA); Remote; USD 180,000 - 240,000; Full time

Job summary

Obsidian leads cutting-edge AI infrastructure, seeking Cloud/DevOps Engineers to strengthen Kubernetes operations, IaC pipelines, and AWS service integrations. You will contribute to robust, scalable AI training and inference platforms within a full-time role.

Responsibilities include guiding teams, designing diagnostic tasks, and building evaluation rubrics while collaborating with domain experts to ensure quality and reliability of the deployment stack.

Qualifications

• 4+ years of professional cloud infra/DevOps or platform engineering experience.
• Hands-on production Kubernetes operations; not just manifests.
• Experience with Infrastructure-as-Code (Terraform or AWS CDK).
• Experience integrating AWS services in production (Lambda, API Gateway, DynamoDB).
• Experience building and owning CI/CD pipelines.
• Demonstrated career progression.
• Availability for at least 40 hours/week during weekdays.
• Strong written communication and ability to explain complex decisions.

Responsibilities

• Guide research and engineering teams to close knowledge gaps and improve AI model performance in cloud infra, Kubernetes ops, and IaC.
• Design tasks and write solutions to cluster diagnosis, AWS service integration, and infra automation problems.
• Evaluate infra engineering tasks and provide clear technical feedback.
• Develop rubrics to assess cluster failure diagnosis, IaC design quality, and CI/CD pipeline reasoning.
• Collaborate with experts to ensure training data accuracy.

Skills

Kubernetes

Cloud infrastructure

DevOps

Site reliability

CI/CD pipelines

Cloud-native architecture

Tools

Kubernetes

Terraform

AWS CDK

AWS Lambda

API Gateway

DynamoDB

Job description

Obsidian leads cutting-edge AI infrastructure, seeking Cloud/DevOps Engineers to strengthen Kubernetes operations, IaC pipelines, and AWS service integrations. You will contribute to robust, scalable AI training and inference platforms within a full-time role.

Responsibilities include guiding teams, designing diagnostic tasks, and building evaluation rubrics while collaborating with domain experts to ensure quality and reliability of the deployment stack.