How AI is changing your work
Simple, repetitive calls and chats are moving to AI voice bots and chatbots, while humans handle complex cases.
Companies deploying these bots need people to write and test conversation flows, review AI mistakes and improve the knowledge base the AI draws on.
Engineers who can connect AI to CRM systems, call transcripts and ticketing tools are in demand across BPO and CX companies.
What you already bring to AI
Real customer conversations
Knowing how users actually phrase problems, which is essential for testing and improving AI agents.
Process & escalation rules
Designing when an AI agent should hand over to a human.
Quality & CSAT metrics
Defining how to measure whether an AI agent is doing a good job.
Communication skills
Writing clear prompts, guidelines and documentation.
Your 6-month roadmap
Same live classes as every other learner, with the examples, projects and interview preparation angled toward where you're coming from.
- Months 1–2
Computer and Python basics from absolute zero, with daily practice exercises.
- Month 3
How AI understands text: NLP, intent classification, sentiment.
- Months 3–4
Build a support chatbot that answers from a knowledge base (RAG).
- Months 4–5
AI agents that look up orders, create tickets and hand off to humans.
- Months 5–6
Deployment, portfolio, resume and interview preparation for your first tech role.
Roles you can target
Conversational AI developer
Build and improve chatbots and voice agents.
GenAI engineer (CX automation)
RAG over support knowledge bases, agents connected to CRMs.
AI quality analyst
Evaluate and improve AI conversations, a common first step.
The honest challenges
A career switch into AI is very doable, and it isn't easy. Here is what to expect:
- This is a big jump. Expect to practise 1–2 hours a day, especially in the first two months.
- Night shifts make live classes hard. Use recordings and weekend sessions.
- Your first tech role may be an AI quality or junior developer role before an engineer title.
- Graduates generally have an easier time with hiring filters than non-graduates. Ask us about your situation honestly.
Projects in your portfolio
- Production RAG chatbot over private company documents
- Multi-agent workflow built with LangGraph
- Fine-tuned domain-specific LLM
- NLP service serving live predictions through FastAPI
- Full MLOps deployment on AWS with CI/CD and monitoring