8-Week Roadmap to a $200K+ AI Engineering Role

Bashiri Smith · Facebook reel · 2026-09-19 · 0:06 · 43,095 views · Open on Facebook

Topics: Start Here: Roadmaps & Strategy, AI Agents, Tool Use & MCP, Resume, Job Search & Interviews · Level: beginner

Summary

The creator lays out an 8-week, self-directed plan for becoming a hireable AI engineer without a bootcamp. It moves from how LLMs work in production, through RAG, embeddings and vector databases, then agents (LangGraph, CrewAI, Claude Code, MCP), LLMOps and evals, and deployment with Docker and FastAPI. It ends with portfolio building, interview prep and applying for jobs. The full plan is in the on-screen caption. The spoken audio is only a short motivational line.

Key points

• Week 1: Learn how LLMs work in production, not just the theory.
• Week 2: Build your first RAG pipeline from scratch.
• Week 3: Learn APIs, vector databases and embedding models.
• Week 4: Build AI agents and orchestrate them with LangGraph and CrewAI.
• Week 5: Learn Claude Code, MCP (Model Context Protocol) and agentic workflows.
• Week 6: Learn LLMOps: evals and monitoring in production.
• Week 7: Containerize your stack with Docker and deploy it with FastAPI.
• Week 8: Build your portfolio, prepare for interviews and apply. The creator says no bootcamp is needed and that knowing what to build matters more than being smarter.

Resources mentioned

• LangGraph · tool · langchain.com · free
  Open-source library for building stateful LLM workflows as graphs, with branching, loops and human-in-the-loop pauses.
  Also in: Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), LangChain vs. LangGraph Explained with One RAG Chatbot (Bashiri Smith on Facebook · notes), Wannabe vs $200K+ AI Engineer: RAG, Agents, Context and Fine-Tuning Mistakes (Bashiri Smith on Facebook · notes), 7 Habits to Become an AI Engineer: Books, Tooling, Research & Shipping (Bashiri Smith on Facebook · notes) and 2 more
• CrewAI · tool · crewai.com · free
  A framework for role-based multi-agent teams.
• Claude Code · tool · code.claude.com · paid · recommended by both Bashiri Smith & Melvin Vivas
  Build agents and pipelines from the terminal; the guide's main agentic coding tool.
  Also in: Create Claude Code Plugins with /plugin-authoring (Melvin Vivas on X · notes), Claude Code mods: customize behavior and UI with plugins (Melvin Vivas on X · notes), AI Engineer Roadmap Overview: From ML Foundations to RAG, Agents & Ops (Bashiri Smith on Facebook · notes), SkillsBento: Free Plugin Marketplace for Codex and Claude Code (Melvin Vivas on X · notes) and 101 more
• Model Context Protocol (MCP) · docs · modelcontextprotocol.io · free · recommended by both Bashiri Smith & Melvin Vivas
  An open standard for connecting LLM apps and agents to tools and data sources. The official docs explain how it works and how to build servers and clients.
  Also in: Grok Bot Templates: Sharing, Publishing and Safely Installing Bots (Melvin Vivas on X · notes), Paste Documentation URLs into Codex Instead of Using MCP (Melvin Vivas on X · notes), OpenAI Agents API: Hosted Codex Harness for Long-Running Cloud Agents (Melvin Vivas on X · notes), Grok Bot Templates: How to Share, Publish, Install and Check Bot Blueprints (Melvin Vivas on X · notes) and 7 more
• Docker · tool · docs.docker.com · free · recommended by both Bashiri Smith & Melvin Vivas
  Containerize everything you ship.
  Also in: Deploying AI workflow integrations with Apache Camel in Docker (Melvin Vivas on X · notes), Devin's cloud Ubuntu sandbox ships with Docker pre-installed (Melvin Vivas on X · notes), 7 Habits to Become an AI Engineer: Books, Tooling, Research & Shipping (Bashiri Smith on Facebook · notes), AI Engineer Roadmap for 2026 in 60 Seconds (Bashiri Smith on Facebook · notes) and 5 more
• FastAPI · tool · fastapi.tiangolo.com · free
  Wrap your models as real inference APIs.
  Also in: Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), Software Engineer to AI Engineer: Job Boards, Stack, Projects and Learning Sites (Bashiri Smith on Facebook · notes), AI Engineer Roadmap for 2026 in 60 Seconds (Bashiri Smith on Facebook · notes), AI Engineer Roadmap: Fundamentals, RAG, Agents, Books & Your First AI Service (Bashiri Smith on Facebook · notes)
• Bashiri Smith's '200k' full roadmap breakdown · pdf · free
  The creator's detailed version of the 8-week AI engineer roadmap, sent to viewers who comment on the post.
  DM only: comment 200k on this reel on Facebook and you get it by DM.

Try this

• Follow the 8-week plan one week at a time: LLMs → RAG → APIs, vector DBs and embeddings → agents → Claude Code and MCP → LLMOps and evals → Docker and FastAPI deployment → portfolio, interview prep and applying.
• Build a RAG pipeline from scratch in Week 2.
• In Week 8, put together a portfolio, prepare for interviews and apply to AI engineering roles.
• Comment "200k" on the post to receive the creator's full breakdown.
• Build a RAG pipeline from scratch.
• Build an AI agent system orchestrated with LangGraph or CrewAI.
• Containerize an AI app with Docker, serve it with FastAPI, and add evals and monitoring.