I'm a Senior Data & AI Engineer with 7+ years of experience architecting scalable data pipelines, MLOps infrastructure, and production-grade AI applications. Currently building AI for security surveillance at NewSense Eng. in Munich and finalizing my M.Sc. in Data Science at FAU Erlangen-Nuremberg.
- π Currently working on 3D perception models and RAG-based LLM applications for enterprise use
- π± Specializing in Generative AI, RAG architectures (LangChain, FAISS, Pinecone), and model evaluation (LangSmith / RAGAS)
- π 1st Place β Adidas Data Science League, Herzogenaurach (2024)
- π Founder of iPractest.com β an AI-powered language learning platform
- π Published in Elsevier β Information Sciences on cluster-oriented instance selection
- π£οΈ Languages: English, Hindi, Urdu (Fluent) Β· German (A2) Β· Bangla (Native)
Languages
ML / AI / LLMs
Data Engineering & MLOps
Cloud, Infra & Backend
AI Application Engineer β NewSense Eng., Munich Β· Sep 2025 β Present Building AI security surveillance applications with Angular + FastAPI + gRPC. Improving 3D perception models for computer vision and developing RAG-based LLM apps with LangChain, FAISS, and Pinecone.
Lead Data & AI Engineer β Mi-C3 Int. Ltd., Malta Β· Feb 2023 β Aug 2025 Designed real-time ETL pipelines with PySpark integrated into Snowflake. Deployed orchestrated workflows on Docker + Kubernetes. Built monitoring stacks with Grafana, Superset, and Pub/Sub. Shipped an AI chat agent for client information retrieval using LLM + RAG + LangChain.
Data Engineer / Software Engineer β SincoS Automation Technologies, Dhaka Β· Nov 2019 β Feb 2023 Built IoT data pipelines with AWS Glue, trained anomaly-detection models on SageMaker, and developed full-stack Spring Boot + React/Angular applications including cross-platform mobile apps in Flutter.
| Project | Description | Stack |
|---|---|---|
| RAG Document Assistant | LLM retrieval system for enterprise documents | LangChain Β· FAISS Β· OpenAI API |
| Anomaly Detection | Production anomaly detection with retraining loop | XGBoost Β· SageMaker Β· Kubernetes Β· MLflow |
| Soap Hardness Prediction | Predictive ML pipeline with automated retraining | Databricks Β· MLflow Β· XGBoost |
| Energy Monitoring System | Real-time IoT monitoring with ML insights | Airflow Β· DBT Β· RabbitMQ Β· Angular |
| Telecom Tower Data Processing | Streaming pipeline for telecom infrastructure | NiFi Β· RabbitMQ Β· PostgreSQL Β· AWS |
| iPractest.com | AI-powered language learning platform | LangChain Β· Hugging Face Β· React Β· Flask |
- Cluster-oriented instance selection for classification problems β Elsevier, Information Sciences (2022)
- Solving multi-class classification tasks with classifier ensemble based on clustering β UIU Institutional Repository (2019)
- π’ NVIDIA Certified Professional: Agentic AI
- π₯ 1st Place β Adidas Data Science League (Herzogenaurach, 2024)
- π Machine Learning with Python β Coursera
- βοΈ Certified Blockchain Developerβ’ β Blockchain Council
π‘ Open to collaborations on Generative AI, RAG systems, and scalable data infrastructure.

