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ProCogia

Builds data platforms and AI systems for enterprises

AI Applied & Agentic AI Intern

AI Application Engineering +1Confirmed live in the last 24 hours
Internship · Winter 2026Vancouver, BC, Canada$23 /hr

About the Job

Requirements

  • Applicants must be currently enrolled in their final year or have recently completed a Bachelor's, Master's, or PhD program in Computer Science, Machine Learning, AI, Data Science, Computational Linguistics, or a related field.
  • Strong Python programming skills and solid software development, debugging, testing, and version-control fundamentals are required.
  • Foundational full-stack experience building frontend, backend, APIs, and integrated application components is required.
  • Familiarity with React and backend frameworks such as Node.js or FastAPI is required.
  • Applicants must be able to turn AI prototypes into functional, end-to-end applications for real users.
  • Hands-on exposure to generative AI, large language models, AI agents, machine learning, or workflow automation is required.
  • Applicants must meet all SWPP eligibility conditions: be a Canadian citizen, permanent resident, or person granted refugee protection in Canada; be enrolled as a full-time student at a recognized Canadian post-secondary institution for the placement; and be legally entitled to work in Canada. International students are not eligible for SWPP-funded placements.

Responsibilities

  • Design, build, test, and improve AI agents and agentic workflows for internal and client-facing solutions.
  • Develop retrieval-augmented generation pipelines that provide grounded responses with citations and traceable source information.
  • Integrate commercial and open-source large language models into applications using APIs, SDKs, and enterprise systems.
  • Define benchmarks, measure quality, identify failure modes, and improve system performance using an evaluation-driven development approach.
  • Build AI solutions with observability, auditability, traceability, and human oversight in mind.
  • Develop integrations with APIs, databases, cloud services, and other enterprise technologies.
  • Troubleshoot and improve workflow accuracy, reliability, latency, and overall performance.
  • Apply software engineering practices including testing, version control, modular development, and documentation.
  • Experiment with emerging tools and frameworks across AI agents, orchestration, retrieval, and model evaluation.
  • Collaborate with consultants, engineers, and data scientists to turn prototypes into scalable solutions.
  • Share work through technical documentation, demonstrations, and presentations.

Desired Qualifications

  • Experience with large language model application development or prompt engineering is an asset.
  • Experience with AI agents or orchestration frameworks is an asset.
  • Experience with Model Context Protocol is an asset.
  • Experience with retrieval-augmented generation architectures or vector databases is an asset.
  • Experience with AI evaluation and benchmarking is an asset.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform is an asset.
  • Experience with Docker or containerized applications is an asset.
  • Experience with open-source large language models is an asset.
  • Experience building software products, side projects, research projects, or technical prototypes is an asset.
  • Prior experience with Python, OpenAI and Anthropic models, open-source large language models, Model Context Protocol, LangChain, LangGraph, Langfuse, cloud platforms, and containerized environments is not expected for all technologies.

About the Company

ProCogia

Builds data platforms and AI systems for enterprises

ProCogia designs, builds and runs data platforms, analytics and AI systems for enterprises in regulated fields such as life sciences, financial services, telecom and the public sector. Its consultants handle AI strategy and governance, data engineering, cloud migration, business intelligence dashboards, machine learning and generative AI assistants that automate workflows. Clients pay for consulting projects and for ongoing managed services, where a standing team monitors, tunes and extends data and AI systems after the first release. Its teams work across major cloud and data platforms, including Snowflake, Databricks, Google Cloud and Microsoft Azure. ProCogia was founded in 2013 and is headquartered in Vancouver, British Columbia.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Vancouver, Canada
Founded
2013

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