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Project Overview

To advance the organizations capabilities in Generative AI through hands-on research, experimentation, and development of prototype solutions that leverage large language models, multimodal AI systems, and data engineering techniques.

The intern will join the AI R&D team to assist in generative AI experimentation and development. This project will focus on identifying promising AI techniques, improving model performance through better data and evaluation methods, and building small-scale prototypes to demonstrate new capabilities.

Key Responsibilities

• Conduct literature reviews on emerging generative AI research and tools.

• Annotate and curate datasets for model training and fine-tuning.

• Evaluate and document model outputs for quality, accuracy, and bias.

• Develop or refine data pipelines for automated testing and model evaluation.

• Contribute to prototype development and internal demos.

• Present findings and recommendations to the AI R&D team.

Learning Outcomes & Impact

The intern will gain hands-on experience with large language models, prompt engineering, dataset curation, and pipeline automation.

Intern will also gain valuable experience in working with experienced Subject Matter Experts, Data Scientists and/or Data engineers.

Minimum Qualifications

• Currently enrolled in a college/university pursuing a Bachelor's level degree.

• Strong analytical and problem-solving skills to drive analytic insights and/or workflow automation.

• Expected to have data wrangling skills.

• Proficiency in programming languages like Python or R.

• Familiarity with Retrieval Augmented Generation (RAG) architectures and Large Language Models (LLM).

Preferred Qualifications

• Full-time rising senior or graduate student.

• Designing and developing AI agents, implementing agentic workflows.

• Agentic AI frameworks such as LangGraph and standards such as Model Context Protocol (MCP).

• Text mining and Natural Language Processing techniques such as Named Entity Recognition and Text Classification.

• Graph Analysis tools such as Neo4J and Cypher.

• Databricks, Azure AI Foundry, Amazon Bedrock, Amazon SageMaker.

• Process Automation, Image Analysis, Predictive and Prescriptive analysis.

• Understanding of applied machine learning methods and algorithms.

• Exploratory Data Analysis and Workflow Improvement.

• Data-oriented personality with proficiency in using data query languages such as SQL and ability to understand various data structures and common methods in data transformation.

Belong, Connect and Grow at KBR

At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of teams philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver Together.

KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.