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AI & Automation Engineer Roadmap

Developers who want to build autonomous agents, implement RAG systems, and automate workflows using LLMs and tools like N8N.

Timeline
3 to 5 months.
Avg Salary
$100,000 - $180,000+
Freelance
Massive. Every business wants to 'add AI' to their workflow.
Remote Work
Extremely High.

Stage 1: AI Foundations & APIs

30 Days

Understand how to talk to LLMs programmatically.

Week 1: Prompt Engineering

Learn how to write deterministic prompts.

Few-Shot PromptingChain of ThoughtSystem Prompts

Week 2: OpenAI & Anthropic APIs

Connect to LLMs using code.

Function CallingStreamingToken Management

Stage 2: RAG & Vector Databases

30 Days

Give your AI long-term memory and company data.

Week 3: Embeddings

Convert text to numbers for semantic search.

Text-Embedding-3Cosine SimilarityChunking Strategies

Week 4: Vector Databases

Store and retrieve embeddings.

PineconeSupabase pgvectorChromaDB

Stage 3: Agents & Automation

30 Days

Build AI that can take actions.

Week 5: LangChain & LlamaIndex

Frameworks for building complex AI apps.

AgentsToolsMemoryRetrieval

Week 6: N8N & Workflow Automation

Build no-code/low-code AI pipelines.

WebhooksN8N AI NodesZapier Integration

Projects to Build

  • PDF Chatbot
    Upload a PDF and chat with it using RAG.
    Target: Embeddings & Vector DBs
  • Automated Customer Support
    An N8N workflow that reads emails, generates a draft reply via LLM, and saves it in Slack.
    Target: N8N & APIs

Common Mistakes

  • Training custom models when a simple prompt + API call would work.
  • Ignoring context window limitations and token costs.
  • Not understanding Vector Embeddings and how semantic search works.

Portfolio Tips

  • Build tools that save actual business hours (e.g., automated invoice parsers).
  • Include a breakdown of your token costs and latency in your README.

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