About ProCogia:

ProCogia is a data and AI consulting firm helping organizations turn complex technology challenges into measurable business outcomes. We work across highly regulated and high-stakes industries, including telecommunications, financial services, life sciences, healthcare, and the public sector, where security, governance, reliability, and performance are critical. Our teams bring together expertise across data science, engineering, AI, analytics, and consulting to design and deliver practical, production-ready solutions. We are actively advancing capabilities across generative AI, agentic systems, workflow automation, AI governance, and enterprise AI applications. At ProCogia, you will work alongside experienced practitioners on meaningful technical challenges and contribute directly to both client solutions and the platforms and products we are building internally.

Our Core Values: Trust, Growth, Innovation, Excellence, and Ownership

DevOps & Cloud Platform Intern

ProCogia | Vancouver, BC | Consulting | In-Person | Full-time | 40 hours/week

Co-op Term: December 2026–April 2027

Location: Vancouver (On-site – Full-Time Work from office in Vancouver, five days a week Mon-Fri)

Job Summary

ProCogia is looking for a DevOps & Cloud Platform Intern to join our Winter 2027 internship cohort. This role is designed primarily for final-year Bachelor’s and Master’s students who want hands-on experience across cloud infrastructure, DevOps, platform engineering, automation, containers, and AI infrastructure. You will work alongside our Cloud Platform Engineer on real engineering initiatives and learn how modern environments are designed, deployed, operated, and improved. You will also work closely with our AI Applied and LLM Research interns, building the infrastructure that helps them develop, test, and deploy AI solutions. We do not expect prior production experience or knowledge of every technology in our stack. We value strong fundamentals, curiosity, problem-solving, ownership, and the ability to learn quickly through documentation, experimentation, and mentorship.

Key Responsibilities

Support cloud environments primarily on AWS, with exposure to other platforms.
Assist with Infrastructure as Code, environment provisioning, and automation.
Build and improve CI/CD pipelines and deployment workflows.
Build, deploy, and troubleshoot applications using Docker, with exposure to Kubernetes.
Work with Linux environments and strengthen command-line troubleshooting skills.
Support networking, IAM, permissions, secrets, authentication, and cloud security fundamentals.
Assist with monitoring, logging, alerts, incident investigation, and reliability improvements.
Build reusable scripts, templates, automation, and technical documentation.
Participate in technical discussions, demos, architecture reviews, and knowledge sharing.

AI & LLM Infrastructure

You will help create the platform foundation for our AI and LLM teams by:

Setting up AI and LLM development environments.
Containerizing and deploying models, APIs, prototypes, and services.
Supporting cloud compute and GPU environments where applicable.
Automating application and model deployment workflows.
Troubleshooting infrastructure, containers, dependencies, and environments.
Supporting experimentation with LLMs, RAG, agents, and generative AI.

The objective is to learn platform engineering by making AI development faster, repeatable, and reliable.

What You Bring

Final-year Bachelor’s or current Master’s student in Computer Science, Software Engineering, Computer Engineering, IT, Data Science, or a related field.
Interest in DevOps, Cloud, Platform Engineering, Infrastructure, or SRE.
Familiarity with Linux, Git, cloud concepts, and Docker.
Experience with Python, Bash, PowerShell, Go, JavaScript, or another scripting/programming language.
Strong troubleshooting, problem-solving, communication, and learning skills.

Nice to Have: Exposure to one or more of:

Cloud & DevOps: AWS/Azure, Kubernetes, Terraform, CI/CD, networking, IAM, observability.