DevOps & AI Engineering Intern (Undergraduate)

WEX•Chicago, IL

4d•Hybrid

About The Position

We are seeking a highly motivated undergraduate student in Computer Science, Software Engineering, Information Technology, or a related field to join our Engineering teams as an intern. In this role, you will work at the intersection of Developer Enablement and AI Infrastructure—supporting teams that build enterprise developer velocity, cloud migration, SDLC security, and state-of-the-art Model Context Protocol (MCP) servers, agentic frameworks, and AI observability tools across WEX. Working alongside experienced platform engineers, architects, and product managers, you will solve real-world platform challenges using technologies like Python, Git, AWS, Azure, Terraform, GitHub Actions, Artifactory, and modern GenAI developer tools. Our culture is autonomous, collaborative, and passionate about technology—offering high ownership with a strong safety net and direct mentorship from senior engineers.

Requirements

Currently pursuing a Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
Foundational proficiency in Python (including standard data structures, object-oriented concepts, and API integrations) or other modern programming/scripting languages (Bash, JavaScript/TypeScript, Java, Go).
Hands-on experience navigating GitHub and executing CLI workflows (git pull, push, commit, checkout, branch, merge, PRs) for coursework, personal projects, or open-source contributions.
Core understanding of networking concepts (HTTP/HTTPS, REST APIs, basic request/response flows) and systematic technical troubleshooting skills (reading error logs and debugging).
Clear written and verbal communication skills with a service-oriented approach to helping internal developer peers remove friction.
High curiosity, initiative to independently research and troubleshoot technical issues before escalation, and a strong passion for learning modern technologies and AI.

Nice To Haves

Exposure to cloud platforms, networking concepts, containerization (Docker, container registries), or core AWS services (S3, EC2, Lambda).
Familiarity with continuous integration/deployment concepts, editing YAML configuration files, and GitHub Actions (or ARC runner scaling).
Conceptual knowledge or hands-on exposure to tools like Terraform.
Practical experience or strong interest in Generative AI tools, LLM APIs, harnesses, agentic frameworks (e.g., LangChain, LlamaIndex), or AI coding tools (Cursor, Augment, Claude).
Awareness of package managers (npm, PyPI, Maven, NuGet) or enterprise artifact repositories like JFrog Artifactory.
Exposure to software supply chain security, secret push protection, dependency scanning, or AI security guardrails.
Prior experience with ticketing systems, customer support, peer tutoring, or IT helpdesk roles.

Responsibilities

Build & Support AI Infrastructure: Assist in developing, deploying, and maintaining MCP (Model Context Protocol) servers, agentic infrastructure, and AI observability capabilities for the Software Development Life Cycle (SDLC).
Modernize CI/CD & Pipelines: Audit, upgrade, and test GitHub Actions dependencies, converting legacy steps into documented, reusable workflow templates for the internal developer marketplace.
Automate Infrastructure with Code: Write and refactor production-ready Terraform modules to automate Artifactory repository setups, RBAC policies, lifecycle rules, and cloud infrastructure.
Support Enterprise Developer Workflows (OPEX): Provide front-line assistance to internal developers by investigating, triaging, and resolving incoming GitHub, Artifactory, and CI/CD support tickets while maintaining team SLAs.
Integrate GenAI & Agent Frameworks: Evaluate and implement Generative AI tools (e.g., Cursor, Augment, Claude, LangChain, LlamaIndex) to automate engineering workflows and build practical backend services.
Enforce SDLC Security & Metadata Standards: Help implement automated compliance tagging (e.g., FABRIC_ID), native Secret Push Protection, and security guardrails against AI-era threats (such as prompt injection and malicious package dependencies).
Author Technical Documentation & Starter Guides: Create clear README files, sample developer starter repositories, and step-by-step documentation showcasing secure pipeline patterns and AI tool integration.
Collaborate & Engage in Daily Agile Syncs: Participate actively in daily standups and engineering design sessions, articulating technical blockers clearly, sharing progress, and collaborating across distributed, remote teams.