AI Agent Development
Autonomous AI agents that plan, reason, and execute multi-step tasks — plus MCP servers that let models act safely and reliably in production.
- LangGraph
- MCP
- Tool use
- AWS Bedrock
Senior Software & AI Engineer
I build scalable software, AI-powered applications, autonomous AI agents, and production-ready machine learning solutions. 9+ years turning hard problems into reliable products.
Owner & BuilderExpense Copilot AI MCPAn AI-powered expense copilot that turns natural-language conversations into a simpler way to understand and manage spending.Over 9+ years I've shipped production systems end to end — designing resilient backend architectures, then moving deep into applied AI: fine-tuned LLMs, retrieval pipelines, and autonomous agents that plan, reason, and call tools.
Today I focus on Model Context Protocol servers and AI-powered products — building the infrastructure that lets models act safely and reliably in the real world. I care about systems that hold up well beyond the demo.
Dhaka · Remote
Autonomous AI agents that plan, reason, and execute multi-step tasks — plus MCP servers that let models act safely and reliably in production.
Adapt models to your domain with LoRA, RLHF and DPO, and ground answers in your data with robust retrieval pipelines.
Scalable, production-grade REST and GraphQL APIs, microservices and data layers built to handle real load — in Python, Java and Groovy.
Design and build clean, well-documented REST and GraphQL APIs — with authentication, versioning, rate limiting and OpenAPI specs that other teams can rely on.
Responsive, accessible UIs in Vue and React — from component libraries and design systems to full client-side applications.
End-to-end web applications that tie together a clean frontend, robust backend, and database — delivered as production-ready products.
Flagship AI Product
Owned and built by Tanvirul Islam: an AI-powered expense copilot designed around conversational workflows and Model Context Protocol capabilities.
⬢ Agents
AI agents capable of planning, reasoning, and tool execution across multi-step tasks.
▣ Production
Enterprise website builder with native widgets, AI design matching, AI layout generation, and an AI deploy pipeline.
⌘ MCP
Production Model Context Protocol server that lets Claude and other AI hosts manage WebCommander stores directly — pages, components, publish/deploy and media across 20+ tools.
◫ Production
Build it with AI, make it yours — an AI-driven website builder and CMS that generates pages and sections, then hands full editing control to the user.
⊙ ML
Real-time fraud detection model for a bookings platform, flagging fake orders as they arrive and improving continuously from new labeled data.
Understand the problem, users, constraints and what “good” actually means.
Design the systems, data flow and model approach — with evaluation built in from day one.
Iterate fast with real feedback loops, tests and eval metrics guiding every step.
Deploy, monitor and refine until it holds up well beyond the demo.
Sep 2023 — Present
WebAlive · Remote
Feb 2017 — Sep 2023
Bit Mascot · Dhaka
micro1 · Jul 2026 · AI Interview
IBM · Jun 2026 · MCP & Agents
IBM · Jun 2026 · LLM Fine-Tuning
IBM · Oct 2024 · Specialization
IBM · Oct 2024 · Generative AI
IBM · Sep 2024 · AI Applications
IBM · Nov 2024 · ML Foundations
IBM · Oct 2024 · Generative AI
IBM · 2024 · Data Science
IBM · Sep 2024 · Prompt Engineering
A portfolio of 16 open-source projects spanning LLM fine-tuning, RLHF, MCP & agents, generative-AI applications, and applied ML.
OSS projects
Focus areas
Years on GitHub
Parameter-efficient instruction tuning of a causal LM on CodeAlpaca-20k using LoRA via TRL's SFTTrainer, with completion-only loss masking and SacreBLEU evaluation.
Python · LLM · RLHF
GPT-2 + LoRA reward model trained on chosen vs. rejected preference pairs with TRL's RewardTrainer and a Bradley-Terry pairwise loss; evaluated by win rate.
Python · LLM · RLHF
Fine-tunes GPT-2 with PPO using a sentiment classifier as the reward model and a KL-controlled reference policy — the reinforcement-learning stage of RLHF.
Python · LLM · RLHF
Aligns GPT-2 directly on (prompt, chosen, rejected) preference pairs using Hugging Face TRL's DPOTrainer + LoRA — no separate reward model needed.
Python · LLM · RLHF
Production-ready Model Context Protocol suite over Streamable HTTP, with a FastMCP server, filesystem roots security boundary, sampling, and an AI host that drives the tools.
TypeScript · MCP · Agents
Server-enforced MCP permission management with per-tool risk classification, sandbox path confinement, single-use human approval, and tamper-resistant audit logging.
Python · MCP · Agents
LangGraph agent that analyzes text and autonomously selects and chains writing-improvement tools, served through a Django web interface.
Python · MCP · Agents
Document-aware chatbot that answers questions over PDF content using LangChain and Flask, applying retrieval-augmented generation.
Python · GenAI · NLP
eCommerce recommender combining collaborative and content-based filtering (Surprise, Scikit-learn) for real-time, personalized product suggestions.
Python · Applied ML
Neural Nets · 9 min read
Diffusion · 8 min read
LSTM · 7 min read
RNN · 7 min read
Embeddings · 6 min read
CNN · 8 min read