{ "engineer": "Kazi Mohammed Arsh", "role": "Junior AI Engineer | ML & MLOps Specialist", "location": "Mumbai, India", "focus_areas": ["GenAI & RAG Architectures", "Agentic Workflows", "Azure AI Foundry", "Explainable AI (SHAP/LIME)"], "status": "Open for AI / ML Deployment Roles", "metrics_tracked": { "tcs_enterprise_exp": "2+ Yrs", "records_processed": "6.8M+" } }
# System Background & Engineering Focus
Detailed bio log, enterprise experience, and academic foundation.
> SUMMARY: I am a Junior AI Engineer combining 4 years of enterprise Python and data engineering experience (including TCS) with an MSc in Artificial Intelligence (Distinction) from the University of East London.
Specialized in end-to-end Machine Learning pipeline development, Generative AI solutions, and advanced RAG architectures. Hands-on experience with Azure AI Foundry, Azure ML, and OpenAI models for tuning, evaluation, Explainable AI (SHAP/LIME), and deploying production-grade ML agents.
LangChain, LangGraph, RAG pipelines, and context-aware agentic query execution using FAISS & Chroma.
Azure AI Foundry, Azure ML, FastAPI microservices, Dockerization, and CI/CD pipelines.
Interpretability via SHAP & LIME with SMOTE data imbalance handling and ROC-AUC benchmarking.
Modules: Machine Learning, Deep Learning, NLP, Intelligent Systems, AI Ethics
# Featured Projects & Research Artifacts
ML pipelines, high-throughput models, and XAI implementations.
Customer Churn Prediction (XAI Pipeline)
End-to-end machine learning pipeline benchmarking XGBoost and Random Forest. Applied SMOTE to resolve class imbalance and integrated SHAP/LIME for explainable model interpretations.
Domain Name Price Prediction (MLP Neural Net)
Supervised ML classification pipeline handling 6.8 million dataset records. Utilized NLP text-based feature extraction, tokenization, and an MLP Neural Network architecture.
# Professional Experience Timeline
| Role & Organization | Timeline | Key Technical Contributions |
|---|---|---|
|
AI Engineer (GenAI & Data Ops) Vibrant Minds After School Club |
May 2024 – Jun 2026 | Built agentic workflows & automated query handling pipelines leveraging FAISS/Chroma vector DBs. Optimized text pre-processing for zero-latency completions. |
|
Python Dev & Data Engineer Tata Consultancy Services (TCS) |
Sep 2021 – Sep 2023 | Deployed Python automation scripts integrating enterprise LLM workflows. Maintained over a 95% SLA threshold with zero breaches. Built cloud preprocessing on Linux servers. |
|
Tech Operations Manager Evya Lounge (Part-Time) |
Nov 2024 – Dec 2025 | Applied structured data tracking and operational analytics to manage inventory, staff performance, and business workflows. |
# Tech Stack Matrix
| Domain | Primary Tech Stack | Proficiency / Status |
|---|---|---|
| Generative AI & LLMs | OpenAI GPT, Hugging Face, LangChain, LangGraph, RAG, Prompt Engineering | [██████████] 95% |
| ML & Model Training | Scikit-learn, XGBoost, PyTorch, TensorFlow, Keras, SMOTE, SHAP/LIME | [█████████░] 90% |
| MLOps & Cloud | Azure AI Foundry, Azure ML, MLflow, FastAPI, Docker, AWS CloudWatch | [█████████░] 90% |
| Vector DBs & Data | FAISS, Pinecone, Chroma, PySpark, SQL, MongoDB, Apache Spark | [██████████] 95% |
# Vector DB & RAG Pipeline Simulator
Interactive demonstration of context retrieval via vector similarity search.