AI Data Engineer Intern

Role Summary

Exiger is seeking a highly motivated AI Data Engineer Intern to join our Tech Enabled Services (TES): Research & Delivery team for Summer 2026. Reporting to senior research and delivery leaders, this intern will support applied AI initiatives focused on automation, agentic workflows, and higher-order reasoning tasks using modern NLP and data engineering techniques.

This is a full-time, paid internship designed for students with strong foundations in data science and natural language processing (NLP) who are excited to explore how AI can be operationalized to perform increasingly complex tasks. The role is based in Toronto, Canada, and follows a hybrid schedule.

About Exiger

Exiger is a leading supply chain risk management (SCRM) software-as-a-service (SaaS) company, using data and AI to help organizations intelligently identify and manage risk across business relationships. Exiger’s mission is to make the world a safer and more transparent place to succeed.

In 2025, Exiger was named a Leader in the Gartner® Magic Quadrant™ for Supplier Risk Management Solutions and a Value Leader in the Spend Matters™ Fall 2025 SolutionMap for Third Party Risk Management (TPRM) and Supply Chain Risk Management (SCRM). Exiger’s TES organization applies advanced analytics, AI, and research-driven delivery models to solve complex commercial and operational challenges for customers.

Key Responsibilities

• Support the development and evaluation of agentic AI workflows that automate research and operational tasks
• Work with natural language processing (NLP) techniques to enable AI systems to search, retrieve, and synthesize information from structured and unstructured data sources
• Assist in designing and implementing data pipelines, retrieval mechanisms, and APIs that support AI-driven workflows
• Collaborate with data scientists and engineers to operationalize research concepts into repeatable, scalable processes
• Experiment with large language models (LLMs) to perform higher-order tasks such as:
• Database querying and retrieval
• Information extraction and synthesis
• Multi-step reasoning and task decomposition
• Document findings, approaches, and results clearly for technical and non-technical audiences
• Contribute to a defined project with clear success criteria, aligned to TES research priorities

Qualifications And Required Experience

• Final-year Bachelor’s, Master’s, or PhD student in Data Science, Computer Science, Artificial Intelligence, or a related field
• Demonstrated experience with natural language processing (NLP), including a completed or in-progress NLP-focused capstone project
• Strong programming skills in Python and experience working with data using SQL
• Familiarity with large language models (LLMs), including prompt design, evaluation, or applied use cases
• Foundational understanding of data pipelines, APIs, and production data workflows
• Ability to think critically about complex problems and break them into structured, solvable components
• Strong communication skills and comfort explaining technical concepts clearly

Preferred Qualifications

• Experience experimenting with agentic workflows, retrieval-augmented generation (RAG), or AI automation concepts
• Exposure to cloud environments or data engineering tools
• Background in building systems that bridge research and applied delivery

Why Intern with Us

• Valuable hands-on experience in a dynamic and supportive team
• Mentorship from industry experts
• Hybrid work environment with meaningful in-office collaboration
• Hands-on experience working with experienced Delivery and Data Science teams
• Dedicated mentorship and professional development opportunities
• Exposure to real-world SaaS security, compliance, and risk management challenges
• Inclusive, mission-driven culture focused on impact, learning, and growth
• Networking Opportunities within the organization

Key skills/competency

• AI Automation
• Agentic Workflows
• Natural Language Processing (NLP)
• Data Pipelines
• Python
• SQL
• Large Language Models (LLMs)
• APIs
• Information Extraction
• Cloud Environments