How will this help my resume?

1. Resume Update: New Section

You can add a "AI & LLM Engineering Projects" section between your Technical Skills and Professional Experience (or after your Experience if you want it as recent highlights). This keeps it prominent but clearly distinct from your past leadership roles.

Suggested Section:

AI & LLM Engineering Projects (2025 – Present)
Self-directed study and project development focused on building advanced Generative AI applications using Python, OpenAI API, and open-source LLMs (HuggingFace, Ollama). Practical emphasis on Retrieval-Augmented Generation (RAG), fine-tuning (QLoRA), and multi-agent systems.

  • AI-Powered Web Scraper & Brochure Generator – Built pipeline that scrapes company websites, structures data with embeddings, and generates dynamic marketing content.

  • Multi-Modal Customer Support Agent – Designed chatbot integrating text, voice, and image inputs with function-calling for real-world airline support workflows.

  • Meeting Minutes & Action Item Generator – Converted audio recordings to structured summaries using hybrid open/closed-source LLMs.

  • Code Optimization AI – Developed AI tool to translate Python code to optimized C++ with massive performance improvements (60,000x).

  • Knowledge Worker via RAG – Built internal “AI expert” capable of answering company-specific questions by vectorizing documents and integrating search + generation.

  • Capstone: Autonomous Multi-Agent System – Deployed collaborative agent architecture to identify real-time opportunities and execute notifications autonomously.

Core Skills: Python (LangChain, FastAPI, Gradio), OpenAI API, HuggingFace, RAG, Vector Databases (Chroma, Pinecone), Fine-tuning (QLoRA), Multi-agent orchestration, Deployment strategies.

2. Additional Outputs to Exhibit Skills

Beyond adding this section, you can demonstrate the work you’ve been doing — which is especially valuable since it shows employers real artifacts rather than just course completion.

Suggested Outputs:

a. GitHub Portfolio

  • Create a dedicated AI/LLM repo on GitHub with each project in its own folder (brochure generator, multi-modal chatbot, RAG knowledge worker, etc.).

  • Include README files with project goals, architecture diagrams, and instructions to run locally.

b. Public Demos

  • Deploy small web demos (like you’ve done with CareerGPT) using FastAPI + GitHub Pages or Vercel.

  • Example: A lightweight “company brochure generator” demo showcasing RAG and scraping.

c. Technical Blog Posts (LinkedIn / saadaziz.com)

  • Write breakdowns of each project in simple language:

    • Problem → Tech used → Key results (e.g., “Improved retrieval accuracy by 40% using RAG vs vanilla GPT-4”).

    • Good for recruiters and hiring managers to quickly see your AI skills.

d. Visual Architecture Diagrams

  • Create 1-page diagrams for each project (e.g., Ollama local inference stack, RAG pipeline) — can double as LinkedIn posts or portfolio items.

e. Capstone Walkthrough Video

  • Record a short Loom/YouTube walkthrough (2–3 min) demoing the final autonomous multi-agent project — perfect for resume/LinkedIn links.

f. Skills Page on Resume Website

  • Add a dedicated “AI Engineering” page on saadaziz.com showing projects, code snippets, diagrams, and blog posts — positions you as hands-on and up-to-date.

3. Optional Resume Tweaks

  • Update Technical Skills to highlight Python (AI/LLM focus), LangChain, HuggingFace, OpenAI API, RAG, Vector Databases, FastAPI, Gradio, QLoRA Fine-tuning.

  • In Summary/About, add a one-liner like:
    “Currently focused on Generative AI and LLM engineering, building hands-on expertise in RAG pipelines, fine-tuning, and multi-agent AI systems.”

https://chatgpt.com/c/6887980b-97bc-8326-bf01-608b18c07e26

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