GenAI Engineer Intern: Build LLM Apps & AI Workflows

Interon IT Solutions; Chantilly (VA); On-site; USD 34,000 - 55,000; Full time

Job summary

Interon IT Solutions in Chantilly, Virginia is seeking a hands-on Generative AI Engineer or GenAI Intern to develop AI-powered enterprise and healthcare products. You will work with product and engineering teams to move AI use cases from concept through prototyping, development, testing, deployment and continuous improvement.

The ideal candidate enjoys building real applications with LLMs, RAG, AI agents, APIs, and cloud technologies, not merely prompting.

Qualifications

• Bachelor's or Master's in Computer Science, AI, Data Science, SE, IT or related field.
• Strong Python programming skills; experience with REST APIs, JSON, databases, backend development.
• Understanding of Generative AI, LLMs, embeddings, prompt engineering, RAG, and AI app design.
• Experience or project exposure with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.

Responsibilities

• Design, develop, test, and enhance Generative AI features for Interon products.
• Build LLM-powered applications using platforms such as OpenAI, Azure OpenAI, AWS Bedrock, Anthropic.
• Develop RAG solutions using enterprise documents and structured or unstructured data.
• Build AI agents and agentic workflows with tool calling, context management, and multi-step automation.
• Implement prompt engineering, structured outputs, grounding, guardrails, and response-quality controls.

Skills

Python programming

REST APIs

SQL

Git/GitHub

Problem solving

Communication

Education

Bachelor's or Master's in Computer Science/AI/Data Science/Software Engineering/IT

Tools

FastAPI

Node.js

React

TypeScript

Azure OpenAI

OpenAI APIs

AWS Bedrock

Job description

Interon IT Solutions in Chantilly, Virginia is seeking a hands-on Generative AI Engineer or GenAI Intern to develop AI-powered enterprise and healthcare products. You will work with product and engineering teams to move AI use cases from concept through prototyping, development, testing, deployment and continuous improvement.

The ideal candidate enjoys building real applications with LLMs, RAG, AI agents, APIs, and cloud technologies, not merely prompting.