Teaching Fellow - Agentic AI

Edversity is seeking a technically proficient and student-focused AI Engineer / Teaching Fellow to support its Agentic AI & Automation Engineering program. This role is hands-on and centered on providing technical assistance to students, helping them debug code, complete assignments, and overcome implementation challenges. The ideal candidate will not only have a strong theoretical understanding of AI but also the practical ability to dive into a student’s codebase, diagnose issues, explain solutions clearly, and guide learners toward improved engineering practices.

Key Responsibilities

- Live Class Support: Attend core live sessions alongside the Lead Instructor, providing real-time technical assistance. Monitor and address individual student questions related to implementation without interrupting the main lecture. Identify students who need additional technical help.

- Technical Support and Debugging: Assist students in troubleshooting issues across various technologies including Python, REST APIs, JSON, Git and GitHub, LLM APIs, Claude, n8n automation workflows, agentic AI systems, RAG, pgvector, MCP servers, FastAPI, PostgreSQL, Docker, deployment, OpenTelemetry, observability, AI security, and evaluation. Review student repositories to pinpoint technical problems and guide them toward effective solutions.

- Assignments, Labs, and Projects: Support learners with labs, assignments, and capstone projects by reviewing their implementations and offering practical, technical feedback. Help students grasp concepts related to architecture, reliability, debugging, and production engineering.

- Technical Office Hours: Conduct at least one structured technical support session weekly to address debugging, assignment questions, and implementation challenges that cannot be resolved during live classes. Identify recurring issues and develop FAQs, examples, or technical resources to assist students.

- Collaboration with Lead Instructor: Work closely with the Lead Instructor to identify learning gaps, recurring technical issues, and students who may be struggling. This collaboration allows the Lead Instructor to focus on delivering high-quality teaching while ensuring students receive consistent technical support.

Required Qualifications

- Minimum of 2 years of relevant experience in software development, backend engineering, automation, or AI engineering.
- Strong proficiency in Python and API development.
- Hands-on experience with building applications powered by large language models (LLMs).
- Practical knowledge of agentic AI, automation, and retrieval-augmented generation (RAG).
- Familiarity with GitHub, FastAPI, databases, and Docker.
- Strong debugging and problem-solving skills.
- Ability to clearly explain technical concepts to learners with varying levels of expertise.

Preferred Qualifications and Attributes

- Experience with n8n, MCP, pgvector, or similar technologies is highly desirable.
- Previous teaching or mentoring experience is a plus but not mandatory.
- The ideal candidate is technically strong, patient with learners, excellent at debugging, proactive, responsible, and comfortable reading unfamiliar code.
- Must be able to explain complex concepts simply and identify root causes effectively.
- Should be comfortable taking ownership of student technical challenges and driving their resolution.

Success in This Role

Success will be measured by the timely resolution of student technical questions, quality of debugging and project support, reduction in unresolved issues, minimizing troubleshooting interruptions during lectures, quality of assignment and capstone assistance, improvement in student technical confidence, and strong collaboration with the Lead Instructor.

Candidate Assessment

Shortlisted candidates may be asked to complete a practical exercise involving identifying problems, debugging AI applications, recommending solutions, and explaining these solutions as they would to a student. Candidates should also be prepared to demonstrate AI or automation systems they have personally developed.