AI-Agent Development Co-op

Number of Position(s): 1

Duration: 6 - 12 months

Dates: January 2027 - June 2027 - December 2027

Location: Onsite in San Jose, CA

Educational Requirements

Currently a candidate for a master's degree or PhD in computer science, software engineering, artificial intelligence / machine learning, computer engineering, electrical engineering, or a related field with an accredited school in the US.

What You Will Learn:

This Co-Op position is an engineering-facing experience building AI agents for the optical test organization. You will gain practical knowledge in:

• AI Agent Design: How to design, prompt, evaluate, and harden agent workflows (skills, tools, and guardrails) that engineers actually use in daily ODVT work.
• Tooling and Integrations: Connecting agents to engineering systems - issue tracking, documentation, source control, and test data - so they fetch facts instead of inventing them.
• Test Engineering Context: How Optical Design Verification Testing works: test plans, test cases and lab data
• Software Craft: Python development, version control, structured documentation, tests, and iterating on tools from engineer feedback.
• Fiber Communication Exposure: High-speed coherent optical products, DSP concepts, and how test data is used to judge product performance and reliability.
  
  

• Design, implement, and refine AI agents that help ODVT engineers write test plans and test cases, analyze results, search documentation, and track work.
• Build and maintain agent skills, prompts, and tool integrations (for example MCP servers and Python helpers) used by the team.
• Improve reliability: reduce invented values, add source traceability, tests, and review gates so agent output is safe for lab and reporting use.
• Partner with optical test engineers to identify high-value automation opportunities and turn them into working agent workflows.
• Document how to use the agents, collect feedback, and measure whether the tools save time or improve quality.
  
  

• Proficiency in Python (preferred); additional programming or scripting languages welcome.
• Coursework or project experience with LLMs, AI agents, prompt engineering, retrieval-augmented generation (RAG), or similar.
• Comfort with Git and collaborative software development.
• Ability to write clear technical documentation and explain a technical design to non-software engineers.
• Interest in applying AI to a real engineering team, with a skeptical eye toward correctness - not only academic demos.

Nice to have

• Experience with Cursor, VS Code agent/copilot workflows, Model Context Protocol (MCP), or similar IDE-native AI tooling.
• Familiarity with Jira, Confluence, and Git/Bitbucket (or GitHub).
• Basic understanding of fiber optical communication systems, Digital Signal Processing (DSP), or lab/test data analysis.
• Demonstrated attention to detail and strong problem-solving capabilities.
• Ability to work effectively both independently and as part of a collaborative team.
• Excellent written and verbal communication skills.