DevOps Engineer Intern - Summer 2027

DV Trading•Chicago, IL

2d•$40 - $50

About The Position

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.

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.

Nice To Haves

Coursework or projects involving Kubernetes, Prometheus/Grafana, CI/CD, Terraform/Ansible, or cloud (AWS/GCP/Azure); contributions to homelab or open source.
Thoughtful use of AI coding assistants and interest in agent patterns (tools, guardrails, human review)—not required to ship ML models.

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.