About the Role

Edversity is looking for a technically strong and student-focused AI Engineer / Teaching Fellow to support our Agentic AI & Automation Engineering program.

This is a hands-on technical role.

The Lead Instructor will be responsible for primary teaching and curriculum delivery. The Teaching Fellow will provide the technical support layer for the cohort, helping students with debugging, assignments, projects, labs and implementation challenges.

We are not looking for someone who only understands AI theoretically.

We need someone who can open a student's codebase, understand the problem, debug it, explain the solution clearly and guide the student toward better engineering practices.

Key Responsibilities

1. Live Class Support

Attend core live sessions and support the Lead Instructor.

Monitor technical questions and help resolve individual implementation issues without disrupting the main lecture.

Identify students who require additional technical support.

2. Technical Support and Debugging

Help students troubleshoot:

Python

REST APIs and JSON

Git and GitHub

LLM APIs

Claude Code

n8n and automation workflows

Agentic AI systems

RAG and pgvector

MCP servers

FastAPI and PostgreSQL

Docker and deployment

OpenTelemetry and observability

AI security and evaluation

Review student repositories, identify technical issues and guide students toward appropriate solutions.

3. Assignments, Labs and Projects

Support students with labs, assignments and capstone projects.

Review implementations and provide practical technical feedback.

Help students understand architecture, reliability, debugging and production engineering concepts.

4. Technical Office Hours

Conduct at least one structured technical support session each week.

Handle debugging, assignment questions and implementation problems that cannot reasonably be addressed during the main class.

Identify recurring student problems and create short FAQs, examples or technical resources where needed.

5. Collaboration with Lead Instructor

Work closely with the Lead Instructor to identify learning gaps, recurring technical problems and students who may be falling behind.

Allow the Lead Instructor to focus primarily on high-quality teaching while ensuring students continue receiving strong technical support.

What We Are Looking For

2+ years of relevant software, backend, automation or AI engineering experience.

Strong Python and API development skills.

Hands-on experience building LLM-powered applications.

Practical understanding of agentic AI, automation and RAG.

Comfortable with GitHub, FastAPI, databases and Docker.

Experience with n8n, MCP, pgvector or similar technologies will be highly valuable.

Strong debugging and problem-solving ability.

Ability to explain technical concepts clearly to learners with different skill levels.

Previous teaching experience is preferred but not mandatory.

The Kind of Person We Want

We are looking for someone who is:

Technically strong

Patient with learners

Excellent at debugging

Hands-on rather than theoretical

Proactive and responsible

Comfortable reading unfamiliar code

Able to explain complex concepts simply

Strong at identifying root causes

Comfortable taking ownership

Success in This Role

Success will be measured through:

Timely resolution of student technical questions

Quality of debugging and project support

Reduction in unresolved student issues

Reduction in individual troubleshooting during main lectures

Quality of assignment and capstone support

Improvement in overall student technical confidence and capability

Strong collaboration with the Lead Instructor

Candidate Assessment

Shortlisted candidates may be given a practical student project or broken AI application and asked to:

Identify the problem

Debug the implementation

Recommend a solution

Explain the solution as they would to a student

Candidates should also be prepared to demonstrate AI or automation systems they have personally built.