AI Agent Workflow Intern

We are looking for an AI Agent Workflow Intern to help improve our internal AI agent system. This role will focus on understanding our existing agent workflows, debugging issues, improving system flow, connecting tools, and building lightweight internal interfaces based on team direction. 

This is not a model training or AI research role, and the intern will not be expected to design the entire AI agent system from scratch. Instead, we are looking for someone who can understand an existing AI workflow system, follow product and technical direction, and make practical improvements that help the system run more smoothly. 

What You’ll Do 

Understand existing AI agent workflows, tool connections, rules, inputs, outputs, and handoff logic  

Help improve agent workflow based on team-defined improvement directions  

Debug workflow issues by reviewing output, reproducing errors, and identifying where the process breaks  

Adjust rules, tool configurations, routing logic, and workflow steps under team guidance  

Connect agents with internal tools, APIs, databases, dashboards, or communication platforms  

Build lightweight internal interfaces, dashboards, forms, or testing panels for AI workflows  

Create simple test cases to check whether agent workflows are working as expected  

Document workflow structure, known issues, test results, and improvement recommendations  

Work with product, operations, and engineering team members to turn workflow pain points into practical fixes  

What We’re Looking For 

Current student or recent graduate in Computer Science, Information Systems, Data Science, Engineering, Human-Computer Interaction, or a related field  

Basic to intermediate experience with Python, JavaScript, or TypeScript  

Hands-on experience with AI tools, LLM APIs, agent workflows, automation tools, or tool-using AI applications  

Able to understand and modify existing systems rather than needing to build everything from scratch  

Familiarity with APIs, JSON, webhooks, function calling, or basic tool integrations  

Comfortable debugging technical issues by reading logs, testing edge cases, and documenting findings  

Able to build simple internal tools, dashboards, forms, or testing interfaces  

Strong attention to detail, clear documentation habits, and structured problem-solving skills  

Comfortable following product and technical direction while also suggesting practical improvements  

Nice to Have 

Experience with Codex, Claude Code, or similar tools  

Experience with React, Next.js, Streamlit, Gradio, Retool, or simple internal interface tools  

Experience with n8n, Zapier, Make, Airtable, or other workflow automation platforms  

Experience testing prompts, tool calls, structured outputs, or AI workflow behavior  

Experience building small bots, automations, dashboards, or internal tools  

What We’re Not Looking For 

Someone focused mainly on AI model training or machine learning research  

Someone who only wants to design high-level architecture but does not want to debug details  

Someone who has only used ChatGPT casually with no hands-on technical projects  

A pure frontend developer with no interest in workflow logic or system debugging  

A pure prompt writer who cannot work with APIs, logs, or tool connections  

Example Projects 

Improve an existing AI agent workflow based on team-provided direction  

Add a simple interface to test agent inputs and review outputs  

Build a dashboard showing task status, errors, and workflow results  

Debug why an agent is failing to call the correct tool or hand off correctly  

Connect an existing workflow to an internal database, CRM, or communication tool  

Create test cases for common workflow scenarios and edge cases  

Document current workflow gaps and suggest practical improvements