Build dashboards and panels from existing metrics; add recording rules or queries only with review when appropriate.
Participate in platform upgrades (Kubernetes components, agents, or controllers) following runbooks and change windows.
Support migration of services from bare metal to Kubernetes under mentorship (discovery, manifests/Helm values, networking, cutover planning).
Contribute to internal AI-assisted tooling: use AI thoughtfully (verify outputs, protect secrets and customer data), and help improve safe, tool-based agents that use internal APIs and observability data.
Requirements
Pursuing a BS or MS in Computer Science, Computer Engineering, Information Systems, or a related field
Expected to graduate by Summer 2028
Hands-on Linux fundamentals (shell, processes, logs, permissions, basic troubleshooting).
Networking basics: DNS, TCP/HTTP/S, ports, load balancing vs Ingress at a conceptual level.
Git workflow: branches, merge requests, meaningful commit messages.
Python for automation and scripting; comfortable reading YAML for Kubernetes and CI configs.
Interest in SRE/DevOps practices: reliability, least privilege, documenting what you run.
Preferred: coursework or projects involving Kubernetes, Prometheus/Grafana, CI/CD, Terraform/Ansible, or cloud (AWS/GCP/Azure); contributions to homelab or open source.
Preferred: thoughtful use of AI coding assistants and interest in agent patterns (tools, guardrails, human review)—not required to ship ML models.
Compensation Range: $40.00-$50.00 per hour
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