Intern, Software Engineer AI Agents (Fall/Winter 2026)

About the Role

We are seeking a highly motivated Software Engineer Intern to join our AI Agents team. This team explores, prototypes, and productionizes cutting-edge AI agent technologies to accelerate productivity, automate workflows, and enhance knowledge sharing across the organization. You will work on building and improving AI-powered agents that support a wide range of functions, including software development, fleet operations, and business processes.

This is a unique opportunity to experiment with the latest advancements in large language models (LLMs), agent frameworks, and autonomous workflows, while delivering practical impact in a real-world environment.

Key Responsibilities

• Design, build, and iterate on AI agents that automate engineering, operational, and business workflows
• Develop integrations between LLMs and internal systems, tools, and data sources
• Implement agent workflows involving planning, tool usage, memory, and multi-step reasoning
• Experiment with prompt engineering, evaluation techniques, and model optimization strategies
• Build backend services and APIs to support scalable deployment of AI agents
• Collaborate with engineers and cross-functional teams to identify high-impact automation opportunities
• Evaluate and benchmark emerging AI agent frameworks, models, and tools
• Contribute to internal platforms that enable rapid development and deployment of AI-powered solutions

Qualifications

Required:

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• Strong programming skills in Python (preferred) or other languages such as Go, Java, or JavaScript/TypeScript
• Solid understanding of data structures, algorithms, and software engineering fundamentals
• Familiarity with machine learning or large language models (through coursework, projects, or internships)
• Strong curiosity about AI systems and eagerness to explore new technologies

Preferred:

• Hands-on experience with LLM APIs (e.g., OpenAI, open-source models) or agent frameworks (LangChain, AutoGen, etc.)
• Experience building backend systems, APIs, or distributed systems
• Familiarity with prompt engineering, RAG (retrieval-augmented generation), or vector databases
• Exposure to evaluation methods for AI systems (benchmarks, metrics, human-in-the-loop feedback)
• Experience with cloud platforms (AWS, GCP, Azure) or containerization (Docker, Kubernetes)
• Interest in applying AI to real-world problems such as automation, productivity, and decision-making