Cloud / DevOps Engineer (Infra & IaC)

Cloud engineering expertise for AI

Help improve model reasoning about production infrastructure, Kubernetes operations and infrastructure as code. The role draws on practical engineering experience to strengthen data used in AI training and inference infrastructure work.

Responsibilities

• Identify gaps in models’ cloud infrastructure knowledge with research and engineering colleagues.
• Create difficult tasks about diagnosing clusters, connecting AWS services and automating infrastructure, then write correct, structured solutions.
• Review engineering tasks and proposed answers and give specific written technical feedback.
• Develop guidance and scoring criteria for cluster troubleshooting, infrastructure code design and CI/CD reasoning.
• Coordinate with other specialists to keep training data accurate and consistent.

Production experience

At least 4 years of dedicated professional work in cloud infrastructure, DevOps, site reliability or infrastructure engineering at an established organization is required. Your professional record should demonstrate progression toward greater engineering responsibility, alongside the required depth of hands on production work.

You need hands on Kubernetes operations experience that includes identifying and repairing cluster failures. Experience restricted to writing manifests or relying on a managed control plane is insufficient.

Production infrastructure as code experience must include Terraform, AWS CDK or both. Direct integration of AWS services, including Lambda, API Gateway and DynamoDB, is required, along with ownership of CI/CD pipelines.

Commitment and employment

The role requires 40 hours each week during weekdays, supported by reliable availability and clear explanations of complex engineering decisions.

This is W2 employment through an employer of record partner, with the opportunity to work within an AI laboratory’s extended workforce. The partner administers payroll and benefits for the engagement.