DevOps Engineer Intern - Summer 2027

Overview

As a DevOps Engineer Intern, you'll work directly within a small, global DevOps team that owns firm-wide infrastructure and platform solutions. This is a high-impact, high-visibility role where your work ships to production.

Responsibilities

• Deploy and operate workloads on Kubernetes: containers, Pods, Deployments, Services, Ingress, and basic storage (PV/PVC concepts).
• Work in a GitOps model using Argo CD (or equivalent): reconcile desired state from git, troubleshoot sync and health, propose safe changes via merge requests.
• Extend observability: OpenTelemetry concepts, Prometheus targets and exporters, Grafana dashboards, and Alertmanager routing-always starting in lower environments.
• Triage alerts end-to-end: validate signal, correlate with recent changes, document findings, and escalate with evidence.
• 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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