AI Product Analyst Co-Op (Roux Institute)

Description

The AI Product Analyst Intern supports the Enterprise ERP AI team as it researches, designs, evaluates, and releases AI-enabled capabilities for public-sector organizations.

You will work with Product Managers, Product Owners, Product Analysts, AI Engineers, UX and UI Designers, QA, and Subject Matter Experts. Your work will help the team turn client and user needs into clear product requirements, realistic evaluation scenarios, useful documentation, and evidence for product decisions. Projects may involve AI capabilities embedded in Enterprise ERP workflows.

This is a learning role with meaningful deliverables. You will receive guidance on priorities and methods, then take responsibility for defined research, analysis, documentation, or validation work. The role does not require prior ownership of a software product or deep expertise in public-sector ERP systems.

What You Will Learn

• How an enterprise software team moves an AI use case from discovery through design, evaluation, release, and improvement.
• How AI assistants use product data, curated knowledge, context, tools, and orchestration to support real business workflows.
• How product teams evaluate accuracy, usefulness, risk, user trust, and adoption before and after release.
• How product, engineering, UX, QA, implementation, support, and client stakeholders work together to deliver AI capabilities.

Responsibilities

Product Discovery and Research

• Research user problems, business workflows, market developments, and existing product behavior, and identify where AI could explain, guide, summarize, search, or assist with a task.
• Prepare for client advisory panels, interviews, usability sessions, and product-team discussions, then organize findings into recurring needs, trust concerns, and adoption barriers.
• Draft user stories, acceptance criteria, process flows, and supporting requirements under the guidance of a Product Owner or Product Manager.
• Maintain organized project information in Jira and Confluence and connect research findings to relevant use cases or backlog items.

AI Evaluation and Analysis

• Help create realistic test prompts, expected outcomes, evaluation datasets, and failure scenarios based on Enterprise ERP use cases.
• Run structured evaluations and analyze results, user feedback, and adoption signals for accuracy, completeness, consistency, relevance, and usability.
• Test how AI experiences handle vague requests, unsupported questions, citations, confidence, confirmation, and safe fallback behavior.
• Document observations and recommend follow-up investigation or product improvements for review by experienced team members.

Documentation and Adoption Support

• Draft feature documentation, release notes, FAQs, onboarding guides, and internal training materials.
• Help prepare product demonstrations and presentations for clients, product teams, support, implementation, and other stakeholders.
• Review documentation for clarity, completeness, consistency, and alignment with current product behavior.

Team Collaboration and Project Ownership

• Participate in team planning, refinement, reviews, research discussions, and knowledge-sharing sessions.
• Build working knowledge of generative AI, retrieval-augmented generation, AI evaluation, agent orchestration, Model Context Protocol, and responsible AI practices.
• Complete at least one defined workstream from initial problem framing through analysis, recommendation, or validation, and present the results to the team.
• Ask questions early, communicate risks or uncertainty clearly, and incorporate feedback into subsequent work.

Qualifications

• Currently pursuing an undergraduate, graduate, or doctoral degree in Computer Science, Data Science, Analytics, Management Information Systems, Human Computer Interaction, Business, or a related field.
• Coursework, projects, or prior experience involving product management, software development, business analysis, user research, data analysis, artificial intelligence, or machine learning.
• Strong analytical skills and the ability to turn qualitative or quantitative information into clear findings.
• Clear written and verbal communication, including the ability to explain technical topics to nontechnical audiences.
• Good organization, attention to detail, and the ability to manage defined assignments with regular guidance.
• Curiosity about how local governments, schools, and other public-sector organizations use enterprise software.
• Experience with spreadsheets, data visualization, SQL, or Python is preferred.
• Familiarity with large language models, prompt design, retrieval-augmented generation, Agile development, Jira, or Confluence is preferred.