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Structured Multi-Week Career Blueprint

AI Automation & Prompt Engineering 10-Week Blueprint

Go beyond ChatGPT chats into building production AI applications. Architect Retrieval-Augmented Generation (RAG) vector pipelines, orchestrate multi-agent workflows with LangChain, and leverage Cursor AI for 5x engineering throughput.

Target RoleAI Workflow Developer / Prompt & Automation Architect
Total Duration10 Weeks
Weekly Effort12 Hours / Week
Target CTC₹8.0L – ₹24.0L LPA

Milestone Execution Timeline

Phase 1 • Weeks 1 – 3

Phase 1: LLM APIs, Structured Outputs & System Prompts

Master OpenAI and Claude API integrations, JSON mode, few-shot prompt crafting, and token budgeting.

Key Milestones:
  • Chain-of-thought, few-shot prompting, and XML structural boundaries
  • OpenAI & Claude API parameters (temperature, top_p, max_tokens)
  • Enforcing strict JSON outputs with Pydantic schemas
  • Token cost estimation and rate limit backoff algorithms
🎯 Deliverable Milestone Project: Customer Escalation Triage Bot that analyzes incoming support emails, classifies urgency, and outputs structured JSON action items.
Phase 2 • Weeks 4 – 7

Phase 2: RAG Pipelines & Vector Database Retrieval

Build real-time knowledge retrieval engines connecting proprietary PDF documents, Notion pages, and SQL databases.

Key Milestones:
  • Text embeddings (text-embedding-3-small, Cohere Embed)
  • Chunking strategies (recursive character splitting, semantic chunking)
  • Vector database indexing and hybrid search (Pinecone, ChromaDB, PGVector)
  • Re-ranking search results with Cohere Re-rank for high contextual precision
🎯 Deliverable Milestone Project: Indian Tax & Legal Circulars Assistant: Ask complex GST/RBI questions and get exact citation answers with page references.
Phase 3 • Weeks 8 – 10

Phase 3: Autonomous Multi-Agents & Production Deployment

Orchestrate agents capable of calling external APIs, browsing the web, and executing automated multi-step workflows.

Key Milestones:
  • LangGraph / CrewAI multi-agent state machines and human-in-the-loop approvals
  • Tool calling (function calling) with custom Python scripts and REST APIs
  • Prompt injection defense (input validation, system prompt delimiters)
  • Evaluating RAG quality using Ragas (Faithfulness, Answer Relevance)
🎯 Deliverable Milestone Project: Automated Competitor Pricing Agent: Scrapes competitor product prices daily, analyzes shifts, and drafts an executive briefing deck.

Job-Readiness Graduation Checklist

Built and deployed a live RAG chatbot with verifiable source citations
Implemented structured JSON output extraction with Pydantic validation
Configured automated multi-agent tasks with LangGraph or CrewAI
Published code repositories on GitHub with clean architectural diagrams

Common Career Transitions

Traditional Software Developer → Generative AI Engineer

Existing programming skills make API integration and vector database queries second nature.

Content / Product Strategist → AI Automation Consultant

Strong domain understanding of workflow bottlenecks enables designing high-ROI bots.

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