Teaching Fellow - Agentic AI

Edversity; Islamabad; On-site; PKR 650,000 - 900,000; Full time

Job summary

Edversity is seeking a technically strong AI Engineer / Teaching Fellow to support our Agentic AI & Automation Engineering program. This is a hands-on technical role where the Lead Instructor handles curriculum and the Fellow provides debugging, labs, and project support.

You will open students' code, diagnose issues, explain solutions, and guide best engineering practices. Expect to assist with Python, REST APIs, GitHub, FastAPI, Docker, and LLM integrations, helping learners across skill

Qualifications

• 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.

Responsibilities

• Live Class Support: Attend core live sessions and support the Lead Instructor; monitor technical questions and resolve individual implementation issues.
• Technical Support and Debugging: Help students troubleshoot Python, REST APIs, GitHub, LLM APIs, Docker, FastAPI, PostgreSQL, and related technologies; review repositories and guide solutions.
• Assignments, Labs and Projects: Support students with labs, assignments and capstone projects; review implementations and provide practical feedback.
• Technical Office Hours: Conduct at least one structured technical support session weekly; handle debugging and questions beyond main lectures.
• Collaboration with Lead Instructor: Identify learning gaps and ensure students receive strong technical support while the Lead Instructor focuses on teaching.

Skills

Python

API development

LLM-powered applications

Agentic AI

GitHub

FastAPI

Docker

n8n

pgvector

Tools

REST APIs

Job description

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.