I'm Md Emon Hasan an aspiring top AI/ML engineer driven to build production-grade, enterprise-ready AI systems. My expertise lies in designing multi-agentic architectures with LangGraph orchestration, AgentOps monitoring, and intelligent tool routing — going far beyond prototypes to create systems with reasoning, memory, adaptability, and real-world impact.
I specialize in Generative AI, fine-tuning foundation models, RAG pipelines, and memory-augmented LLMs, consistently aligning my work with industry MLOps standards. With a strong focus on scalability, robustness, and modularity, I craft full-stack AI applications that integrate seamlessly into business workflows.
Designing end-to-end AI/ML pipelines from data to deployable applications.
Crafting modular agentic workflows with memory-integrated generative AI architectures.
Fine-tuning LLMs using LoRA, QLoRA, PEFT, and quantization techniques.
Enabling intelligent decision-making via tools, memory, and multi-agent planning.
Building intelligent systems using structured, labeled, and unlabeled datasets efficiently.
Deploying scalable ML models using Streamlit, FastAPI, and local servers.
I specialize in building full-stack, real-world AI/ML systems using cutting-edge technologies such as Agentic AI, LangGraph, LLM Orchestration, and Multi-Agent Architectures. My work focuses on intelligent planning, reasoning, and tool-augmented AI assistants.
Pursuing BSc in Computer Science and Engineering from City University, Dhaka, Bangladesh. Specialized in Software engineering principles with a focus on real-world applications.
Actively building industry-grade AI systems, participating in research, and contributing to open-source AI/ML projects during academic years (2022 – 2025).
During this phase, I focused entirely on academic excellence in science subjects including Physics, Chemistry, Mathematics, and Biology. While I did not engage in extracurricular activities at this stage, this period laid the foundational knowledge and discipline that later shaped my journey into AI/ML engineering.
Successfully completed the Secondary School Certificate under the Dinajpur Board, laying the academic foundation in core subjects. This stage served as the starting point of my educational journey.
Learned and practiced frontend development fundamentals including HTML, CSS, JavaScript, and responsive UI design. Gained hands-on experience by building static websites, landing pages, and small projects, while developing a strong foundation in web technologies and design principles.
Worked as a Backend AI Engineer focusing on building production-grade multi-agent AI systems. Developed and maintained agentic workflows using LangGraph and AgentOps orchestration. Implemented tool-augmented pipelines (PDFs, Web, APIs, Databases) and integrated memory-driven reasoning systems. Fine-tuned large language models (LLMs) using LoRA, QLoRA, and PEFT for real-world AI applications such as intelligent financial advisors and medical assistants.
How I designed a multi-agent system (Planner, Tool, Memory) with LangGraph to analyze portfolios, fetch market data via tools, and deliver explainable, goal-aware recommendations.
Inside the architecture: symptom triage agent, retrieval-augmented grounding on medical guidelines, citation fidelity checks, and fallback policies to maintain safety while answering patient queries.
A walkthrough of my pipeline for claim parsing, multi-source retrieval, reranking, and structured evidence scoring—plus how I log traces and evaluate reliability with AgentOps.
Savar, Dhaka, Bangladesh