Design and build services in Python that power AI-driven products and shared capabilities.
Build resilient service integrations across internal systems, specifically handling complex failure modes and rate limits.
Develop and evolve LLM-backed features and agentic workflows, focusing on reliability and real-world behavior.
Help build or extend evaluation harnesses, benchmarks, and feedback loops to ensure the high performance of AI-powered features.
Work at a high velocity in two-week sprints and participate in weekly meetups to share technical progress and solve challenges.

Currently enrolled in a program in Computer Science, Software Engineering, or a related quantitative field (graduating in 2027).
Excellent modern Python engineering skills with the ability to write readable, performant, and testable code.
A strong background in AI/ML and experience with independent projects using LLMs, foundation models, or RAG.
A solid understanding of software engineering principles, including APIs, version control, and system architecture.
A genuine curiosity about applying AI to cybersecurity or hands-on experience in the domain.

AI/Machine Learning Engineer Intern

Key skills