Software Engineering Intern - Applied AI (Spring 2027 Co-Op)

Rivian•Palo Alto, CA

4d•Onsite

About The Position

Join Rivian’s AI platform team to build sophisticated, production-grade AI systems and reusable capabilities used across the company. This is a highly technical, high-ownership internship for exceptional candidates who want to advance how Rivian designs, engineers, and delivers its products through LLMs, agentic AI, and machine learning.

Requirements

Must be currently pursuing a masters or PhD degree at an accredited university.
Currently pursuing a degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, or a closely related technical field.
Exceptional Python programming ability and strong software-engineering fundamentals.
Demonstrated experience building technically substantial AI/ML or LLM applications beyond introductory coursework.
Strong foundation in algorithms, data structures, machine learning, statistics, and experimental design.
Ability to independently navigate complex, ambiguous technical problems and deliver high-quality results.
Strong written and verbal communication skills, with the ability to explain technical trade-offs clearly.

Responsibilities

Design and implement sophisticated agentic systems that combine LLMs, tool use, retrieval, memory, and structured reasoning.
Develop multi-agent and long-running workflows using LangGraph, LangChain, LlamaIndex, or equivalent custom architectures.
Build advanced retrieval and knowledge systems using embeddings, vector databases, semantic search, and knowledge graphs.
Create reusable platform components for agent orchestration, context management, evaluation, observability, and human oversight.
Own meaningful technical deliverables from problem formulation and architecture through implementation, testing, and demonstration.
Develop rigorous evaluation frameworks, golden datasets, automated metrics, and regression tests for nondeterministic AI systems.
Integrate AI applications with enterprise APIs, databases, data platforms, and internal software systems.
Perform systematic failure analysis and improve system accuracy, reliability, latency, scalability, and maintainability.
Research emerging techniques in generative AI, agentic systems, and machine learning, then validate their value through disciplined experimentation.
Collaborate with experienced AI engineers, researchers, product teams, and technical domain experts across Rivian.