Data and AI Engineering Intern

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.

 Data and AI Engineering Intern

Electronic Arts is seeking a Data and AI Engineering Intern to join our Data and Analytics team. This internship focuses on applying Generative AI and agentic engineering approaches to modern data engineering, analytics, and automation.

You will work with data engineers, architects, and analysts to build AI-assisted data solutions using Python, SQL, Large Language Models, and cloud data platforms. You will explore how AI agents can interpret requirements, generate and validate code, automate data-quality checks, create technical documentation, investigate anomalies, and support pipeline monitoring with appropriate human oversight.

Key Responsibilities

• Develop Python and SQL solutions for data ingestion, transformation, validation, and analysis.
• Build prototypes using LLMs, prompt engineering, Retrieval-Augmented Generation, embeddings, vector search, tool calling, and agentic workflows.
• Assist in developing scalable ETL/ELT pipelines, data models, APIs, and reusable data products.
• Apply testing, data quality, security, governance, and responsible AI practices.
• Collaborate with technical and business teams and present findings, prototypes, and recommendations.

Required Qualifications

• Pursuing a bachelor’s Degree, Data Science, Artificial Intelligence, Engineering, or a related field.
• Strong fundamentals in Python, SQL, programming, and problem solving.
• Basic understanding of databases, data pipelines, APIs, and Generative AI.
• Familiarity with Git and collaborative software development.

Preferred Qualifications

Exposure to Snowflake, Databricks, Spark, dbt, Airflow, Lang Chain, Lang Graph, Stream lit, cloud platforms, or vector databases is advantageous. Machine Learning experience, including scikit-learn, Py Torch, or TensorFlow, is an additional advantage.