Career roadmap
GenAI Testing Specialist
Go deep on the hardest part of modern QA — testing non-deterministic AI systems.
- Starting level
- Intermediate → Advanced
- Duration
- ~18 hours
- Courses
- 4
- Skills
- 6
Who it's for
Experienced automation engineers, SDETs and QA leads whose teams have started shipping LLM or agent features.
Career outcome
GenAI / LLM Testing Specialist or AI Quality Engineer.
Confidently test LLMs, agents, RAG pipelines, and MCP servers — the skills nobody else is teaching.
Prerequisites
- Comfortable with Python
- Existing automation or API testing experience
Skills you'll gain
- Testing non-deterministic model output
- Bias, fairness and responsible-AI checks
- Prompt stability and regression strategies
- MCP servers and tool wiring
- Multi-agent systems with AutoGen
- Agent orchestration with LangChain and LangGraph
The course sequence
Take them in this order — each step builds on the last.
- 1
Testing Machine Learning and GenAI Systems
Foundations of AI testing — bias, drift, prompt stability.
3 hours · 33 lectures · All Levels · AI / ML Testing
- 2
MCP for QA Engineers: AI Automation with TypeScript (2026)
The protocol that connects AI to real backend systems.
4 hours · 22 lectures · All Levels · AI Protocols
- 3
Agentic AI for QA Automation with Python
Build multi-agent QA systems with AutoGen.
2.5 hours · 20 lectures · All Levels · AI Agents
- 4
Agentic Workflow Using LangChain and LangGraph
Orchestrate agent workflows for complex QA tasks.
4 hours · 26 lectures · All Levels · AI Agents
What you'll build
- 01
A functional and responsible-AI test suite for an ML/GenAI system
- 02
An MCP server that an AI client can call
- 03
A multi-agent QA workflow in AutoGen
- 04
A LangGraph orchestration with human-in-the-loop approval
Related courses
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Other learning paths
Ready to start GenAI Testing Specialist?
Begin with course 1, or ask Tia to tailor the roadmap to your experience.