Agent Systems Intern

What you'll do?

Agent systems development

• Assist in building components of the Aedeon agent fleet parsers, extractors, dependency mappers, test synthesizers under senior engineer guidance.
• Learn how agents operate against the Code Intelligence Graph so every action traces back to a line of code.
• Get exposure to governed autonomy stages (shadow, supervised, autonomous) and the human-in-the-loop controls at each stage.
• Shadow how the team orchestrates foundation models (Anthropic, OpenAI, Google) through the Aedeon Decision Model.

Verification and quality

• Practice writing tests before code, for the small pieces of functionality you own.
• Help build behavior-equivalence checks comparing agent output against expected results.
• Contribute to test cases covering functional flows and edge cases, with mentor review before anything ships.
• Get hands-on with pytest and the team's CI/CD-integrated test suites.

Collaboration and documentation

• Write clear, readable Python and submit pull requests for review.
• Document what you build in Confluence or equivalent clearly enough that a teammate can pick it up without asking you first.

What we're looking for?

Core Python and fundamentals

• Currently pursuing, or recently completed, a degree in Computer Science, Engineering, or a related field.
• Solid foundation in Python personal projects, internships, or coursework count; no minimum years of professional experience required.
• Basic understanding of APIs and web frameworks (FastAPI, Flask, or similar) is a plus.
• Genuine curiosity about LLMs, agent frameworks, and how software gets verified before it ships.

Engineering mindset

• Willingness to learn testing discipline as a habit, not an afterthought.
• Comfortable asking questions and taking feedback on code quality.
• Available to work with reasonable overlap with US business hours.

You'll be preferred if you've

• Coursework or personal projects using LangChain, AWS Bedrock, or similar agentic AI frameworks.
• Any exposure to Docker, basic Kubernetes concepts, or cloud platforms (AWS preferred).
• Familiarity with graph databases (Neo4j) or Elasticsearch/OpenSearch, even at a conceptual level.