🚀 AI / Data & Software Engineer
Specializing in Agentic Systems, Context Engineering, Knowledge Graphs, and Revenue-Driven AI

I design and build production-grade AI systems that go far beyond prompts — combining LLMs, data pipelines, knowledge graphs, and autonomous agents to drive real business outcomes.

Most AI fails because of bad context, bad data, and broken orchestration.
I work where modern AI really lives:

• Context Engineering — structuring memory, retrieval, user state, and business logic so LLMs reason correctly
• Agentic Systems (A2A) — multi-agent workflows where agents plan, delegate, negotiate, and execute
• Graph-based Knowledge Systems — turning unstructured data into reasoning-ready intelligence
• Graph-RAG & Hybrid Retrieval — combining vector search + knowledge graphs for high-precision answers
• MCPs (Model Context Protocols) — designing how models consume tools, memory, and external systems
• AI-Driven Automation — replacing manual workflows with autonomous AI pipelines

• 🧩 Graph-RAG Systems
  Building knowledge graphs over documents, products, users, and interactions to enable deep semantic reasoning

• 🤖 Autonomous AI Agents
  Multi-agent systems using LangGraph + LangChain for sales, research, support, and decision-making

• 🧠 Context & Memory Layers
  Designing long-term memory, user profiles, and behavioral context so agents behave intelligently over time

• 📈 AI for Revenue & Growth
  AI systems for:

  • Lead generation
  • Ecommerce personalization
  • Customer retention
  • Sales automation

• 🔄 AI Orchestration & Automation
  Using n8n / Make to connect LLMs, databases, APIs, and business systems into fully autonomous workflows

• Python, Pandas, NumPy
• TensorFlow, scikit-learn
• OpenAI, Gemini, Claude APIs

• LangGraph
• LangChain
• LangSmith/Ragas/DeepEval/Atla AI/ Posthog
• RAG, Graph-RAG, Tool-Calling, MCPs

• Vector Databases (Pinecone, FAISS, etc.)
• Knowledge Graphs (Neo4j, graph-based schemas)
• Hybrid Retrieval (Vector + Graph + Metadata)

• n8n
• Make.com
• API-based system integration

• Google Cloud
• Azure
• AWS

• MySQL
• SQL Server
• Structured + Unstructured data pipelines

I don’t build chatbots.
I build AI systems.

Systems that:

• Understand users
• Remember past interactions
• Reason over structured knowledge
• Trigger business workflows
• Improve with every interaction

This is how AI becomes a growth engine, not a toy.

🔗 LinkedIn
https://www.linkedin.com/in/sarfaraz-ahmed07

💻 GitHub
https://github.com/Sarfaraz021

The future of AI is not models — it’s context, data, and agent orchestration.
That’s what I build.