Generative AI Engineer & Technology Consultant
Helping Enterprises Solve Complex Problems Using Generative AI, LLMs, and Scalable ML Systems | Computer Scientist
I’m a Generative AI Engineer with experience designing and delivering production-grade systems using large language models (LLMs), retrieval-augmented generation (RAG), and prompt engineering. Currently at IBM Consulting, I’ve built enterprise solutions for intelligent diagnostics, customer experience management, and automated support agents across multiple industries.
- 🧠 Focused on GenAI architectures with LangChain, LangGraph, OpenAI, Pinecone, FAISS
- 🔁 Developed autonomous agents for meeting analytics, medical services, and customer support
- 💼 Experience in AI diagnostics, campaign automation, DevOps, and scalable cloud deployments
- 🎓 Bachelor's in Computer Science from FAST NUCES
- ✍️ Strong communication skills with public content and internal presentations
Package Consultant (AI/ML Focus) – Mar 2023–Present
- Reduced campaign deployment time by 30% through DevOps implementation
- Used UNICA, Interact, and AppConnect for telecom campaigns, improving performance by 20%
- Created shell scripts for incident monitoring and alerting (35% faster response time)
AIML Developer – Innovation Projects (2024)
- Built DB HealthWatch, a diagnostic GenAI agent for database logs (LangChain + GPT-4 + FAISS)
- Reduced diagnosis time by 60%, improved incident classification and proactive alerts
- Implemented multi-agent system for CPU, memory, and I/O analysis with contextual email reports
Developer
- Created a FastAPI + LangChain support bot reducing ticket volumes with automated inquiry resolution
- Integrated OpenAI + Pinecone for fast, accurate responses
- Improved CSAT scores and operational efficiency with 24/7 availability
Developer
- Designed AI assistant for appointment handling, test tracking, and doctor availability
- Built LangGraph-based multi-channel agent (Telegram, WhatsApp, Instagram)
- Reduced clinic load and enhanced engagement with RAG-based architecture
Trainee Machine Learning Engineer – Aug 2022–Nov 2022
- Led Data Observability module for ML pipelines using Soda Core, Airflow, and Great Expectations
- Integrated observability APIs and improved ML debugging capabilities
Team Lead – Oct 2018–Jun 2022
- Conducted technical workshops on web and DevOps
- Mentored student teams and led project-based collaborations
| Category | Tech Stack |
|---|---|
| Generative AI |  LangChain •  LangGraph •  OpenAI GPT • RAG • FAISS • Pinecone |
| Machine Learning |  TensorFlow •  Pandas •  NumPy • Gym |
| DevOps & Infra | AWS • Azure •  Docker •  Kubernetes •  Jenkins •  Airflow |
| Languages |  Python •  JavaScript (ES6) •  C/C++ •  Elixir •  Java •  CUDA |
| Databases |  MySQL •  PostgreSQL •  MongoDB • Oracle •  Supabase • Pinecone • SQL Server |
| Frameworks |  FastAPI •  Node.js •  Express.js •  React •  Streamlit •  Svelte |
| Version Control |  Git •  GitHub •  GitLab •  Bitbucket |
B.S. in Computer Science – FAST NUCES, Peshawar (2018–2022)
Key Courses: Algorithms, OS, Web Programming, Enterprise Systems, AI, Databases
- DB HealthWatch: GenAI platform for automated database issue diagnostics
- XM Support: 24/7 customer inquiry handler using FastAPI, LangChain, Pinecone
- MediCare.AI: AI-powered multi-agent system for patient engagement
- RAG & LangGraph Workflows: Building open multi-agent GenAI systems with LM Studio
- Email: essayyzed@gmail.com
- LinkedIn: linkedin.com/in/essayyzed
- GitHub: github.com/essayyzed
- Website: essayyzed.github.io
- Twitter: twitter.com/essayyzed