AI-Agent Development Co-Op
Posted 4 Sep 2026
Advertised as “AI-Agent Development Co-op”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Internship
No salary listed for this role.
Field of studyArtificial Intelligence, Computer Engineering, Computer Science, Electrical Engineering, Machine learning, Software Engineering (or related)
Study levelMaster's or higher
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:
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AI Agent Design: How to design, prompt, evaluate, and harden agent workflows (skills, tools, and guardrails) that engineers actually use in daily ODVT work.
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Tooling and Integrations: Connecting agents to engineering systems - issue tracking, documentation, source control, and test data - so they fetch facts instead of inventing them.
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Test Engineering Context: How Optical Design Verification Testing works: test plans, test cases and lab data
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Software Craft: Python development, version control, structured documentation, tests, and iterating on tools from engineer feedback.
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Fiber Communication Exposure: High-speed coherent optical products, DSP concepts, and how test data is used to judge product performance and reliability.
Responsibilities
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Design, implement, and refine AI agents that help ODVT engineers write test plans and test cases, analyze results, search documentation, and track work.
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Build and maintain agent skills, prompts, and tool integrations (for example MCP servers and Python helpers) used by the team.
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Improve reliability: reduce invented values, add source traceability, tests, and review gates so agent output is safe for lab and reporting use.
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Partner with optical test engineers to identify high-value automation opportunities and turn them into working agent workflows.
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Document how to use the agents, collect feedback, and measure whether the tools save time or improve quality.
Qualifications
- 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.