About the role

Yodlee Inc. is looking for highly motivated summer interns to join the Analytics Engineering team, with a focus on AI Agent Development. This internship is designed for students who are passionate about data, artificial intelligence, software engineering, and building intelligent systems that can automate, reason, and generate insights from financial data.

As an intern, you will work with experienced analytics engineers, data engineers, and AI/ML practitioners to explore how AI agents, large language models, retrieval-augmented generation, and workflow automation can improve analytics engineering productivity, data quality, insight generation, and operational efficiency.

This is a hands-on internship where you will contribute to real-world projects, prototype AI-powered solutions, and learn how modern data platforms support large-scale analytics and intelligent applications.

What you'll do

 As an Analytics Engineering Intern – AI Agent Development, you may work on projects such as: Design and prototype AI agents that can assist with analytics engineering workflows.

• Build proof-of-concepts using LLMs, RAG pipelines, prompt engineering, and agentic workflows.
• Develop tools that can help generate, validate, optimize, or explain SQL, Python, and data pipeline logic.
• Explore AI-based automation for data quality checks, metadata analysis, documentation, and operational support.
• Work with structured and unstructured data to generate insights, summaries, and recommendations.
• Assist in building APIs, scripts, dashboards, or internal tools to support AI-driven analytics use cases.
• Collaborate with cross-functional teams to understand business problems and translate them into technical solutions.
• Document designs, experiments, findings, and recommendations clearly for technical and business audiences.
• Participate in team discussions, code reviews, demos, and internship showcase presentations

Qualifications

We are looking for candidates who are curious, self-driven, and eager to learn. Ideal candidates should have exposure to some of the following:

• Currently pursuing a degree in Computer Science, Data Science, Software Engineering, Information Systems, AI/ML, or a related technical field. Strong foundation in Python and basic software development practices.
• Understanding of SQL and relational data concepts.
• Interest in Generative AI, LLMs, AI agents, prompt engineering, or RAG architectures.
• Familiarity with data engineering or analytics concepts such as ETL, data pipelines, APIs, and reporting
• Exposure to cloud platforms such as AWS, Azure, or GCP is a plus.
• Experience with tools or frameworks such as LangChain, LlamaIndex, OpenAI APIs, Hugging Face, FastAPI, Streamlit, Flask, Git, or Jupyter notebooks is a plus.
• Strong analytical thinking and problem-solving skills.
• Ability to communicate technical ideas clearly.
• Willingness to learn quickly and work in a collaborative team environment