Intern, Business Analyst (PNPL)

About the Role

We are seeking a motivated and analytical intern to support the enhancement of internal AI-enabled knowledge solutions.

You will work closely with Business Analysts, product owners, and technology teams to evaluate and improve how information is retrieved, referenced, and presented to users. This role provides hands-on exposure to Retrieval-Augmented Generation (RAG), prompt engineering, AI evaluation, knowledge management, and business analysis within a financial services environment.

Key Responsibilities

• Build and maintain evaluation datasets based on real business questions, process documentation, and internal knowledge sources.
• Analyze AI-generated responses for relevance, factual grounding, citation quality, consistency, and usability.
• Identify retrieval or response quality issues and recommend targeted improvements to retrieval strategies, prompting, or knowledge organization.
• Support the review and improvement of document organization, metadata quality, content coverage, and knowledge accessibility.
• Engage stakeholders to gather feedback, document findings, and translate requirements into test cases and improvement recommendations.

Required Qualifications

• Pursuing a degree in Computer Science, Information Systems, Business Analytics, or a related field.
• Strong analytical, problem-solving, documentation, and communication skills.
• Basic programming knowledge in Python.
• Familiarity with APIs, SQL, data analysis, or related technologies.
• Foundational understanding of Generative AI, Large Language Models (LLMs), embeddings, vector search, or Retrieval-Augmented Generation (RAG).

Preferred Qualifications

• Exposure to LangChain, LangGraph, LlamaIndex, or similar LLM application frameworks.
• Familiarity with RAG evaluation, retrieval testing, prompt engineering, or AI quality assessment.
• Familiarity with AWS Bedrock or cloud-based Generative AI platforms.
• Experience with Git, REST APIs, notebooks, or proof-of-concept development.
• Interest in business analysis, knowledge management, process documentation, or workflow optimization.