AI Engineering & Operations Intern

Fuel Cycle•Los Angeles, CA

1d•$0 - $19•Hybrid

About The Position

The AI Engineering & Operations Intern is responsible for building, integrating, and optimizing AI-powered tools and workflows that improve business operations and accelerate decision-making. This role is ideal for someone who is passionate about large language models, prompt engineering, and the practical deployment of AI systems. Working closely with our Product, Engineering, and Operations teams, the intern will help design and ship AI solutions—from prompt design and API integration to monitoring and evaluation—contributing to high-impact internal initiatives.

Requirements

Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, AI/ML, Software Engineering, Information Systems, or a related field.
Previous internship, coursework, or project work involving LLMs, AI application development, or AI/ML APIs.
Self-starter with a growth mindset, eager to learn and contribute.
Comfortable writing Python; familiarity with REST APIs, JSON, and at least one LLM SDK or framework (e.g., LangChain, LlamaIndex, OpenAI SDK).
A team-oriented attitude and willingness to receive and act on feedback.
Hands-on experience (or strong academic exposure) with LLM APIs such as OpenAI, Anthropic Claude, or HuggingFace; familiarity with prompt design, few-shot techniques, and chaining.
Curious and methodical thinker who understands how AI components (models, retrievers, evals, guardrails) fit together to produce reliable, business-ready outcomes.
Able to explain AI system behavior, limitations, and tradeoffs to both technical and non-technical stakeholders.
Comfortable designing test cases and evals to assess AI output quality, and iterating quickly on prompts or architecture based on results.
Organized and able to manage multiple AI workstreams simultaneously, balancing speed of experimentation with documentation and quality standards.

Nice To Haves

Experience with RAG pipelines, vector databases (e.g., Pinecone, Weaviate, pgvector), or semantic search
Familiarity with AI observability or evaluation tooling (e.g., LangSmith, Braintrust, Weights & Biases)
Exposure to agentic frameworks (e.g., LangGraph, AutoGen, CrewAI) or multi-modal AI applications

Responsibilities

Design, build, and iterate on AI-powered features and internal tools using LLM APIs (e.g., OpenAI, Anthropic, HuggingFace) to improve operational efficiency.
Develop and refine prompts, chains, and agents to automate repeatable tasks and augment decision-making workflows.
Translate business requirements into AI-powered solutions, selecting appropriate models, tools, and integration patterns.
Work alongside Product Managers, Engineers, and Business Stakeholders to identify high-value opportunities for AI automation and tooling.
Contribute to internal documentation, runbooks, and stakeholder demos that communicate AI system behavior and outputs clearly.
Design and execute evaluation frameworks (evals) to measure AI output quality, accuracy, and alignment with business requirements.
Monitor deployed AI features for performance, drift, and edge cases; iterate on prompts and configurations to improve reliability and safety.