> Kamruzzman Shuvo • Retail Interactive Technology | DataLab
Senior Software Engineer with extensive experience designing enterprise-grade data platforms, distributed backend systems, and Agentic AI architectures. Currently embedded as an Independent Contractor for Apple Inc. within Retail Interactive Technology, engineering automated ETL pipelines processing 9M+ records/job and building production FastMCP servers and RAG workflows.
# FastMCP Server: Multi-format Box Enterprise Ingestion
from fastmcp import FastMCP, Context
from pydantic import BaseModel, Field
mcp = FastMCP("Apple-RIT-FastMCP-Gateway")
@mcp.tool()
async def retrieve_box_context(
doc_id: str,
query: str,
ctx: Context
) -> dict:
"""Parse Box docs & standardize AI context retrieval."""
ctx.info(f"Ingesting structured Box content for doc: {doc_id}")
return await mcp_box_parser.extract_chunks(doc_id, query)
Specialized in designing enterprise-grade data platforms, distributed backend systems, and Agentic AI architectures.
Senior Software Engineer | AI & Data Platforms
Senior Software Engineer with extensive experience designing enterprise-grade data platforms, distributed backend systems, and Agentic AI architectures. Currently working on Retail Interactive Technology and DataLab Engineering.
Engineering automated ETL pipelines processing 9M+ records/job and building production Model Context Protocol (FastMCP) servers and secure RAG workflows.
Proven track record in architecting modular Python frameworks (FastAPI, Typer, Alembic, SQLAlchemy), scaling vector search with granular RBAC, and establishing robust SDLC practices with automated GitOps CI/CD on Kubernetes and AWS.
Specialized technical domains verified through enterprise delivery across Apple RIT, DataLab, and distributed cloud services.
Architecting autonomous agentic pipelines, FastMCP servers, and low-latency RAG vector architectures.
Enterprise asynchronous Python frameworks, strict schema contracts, task queues, and CLI tooling.
High-throughput ETL pipelines, dimensional star/snowflake data warehouse modeling, and OLAP cubes.
Container orchestration, GitOps CI/CD delivery, automated testing, and scalable cloud microservices.
Proven track record in architecting modular Python frameworks, scaling vector search, and establishing robust SDLC practices.
Coordinated technical operations for the Virtual Internship System; mentored 50+ engineering interns in data analytics, Python development, and software engineering best practices.
Engineered and optimized backend modules for healthcare data aggregation using Django (DRF) and PostgreSQL, reducing analytics query latency by 35%.
Participated in end-to-end SDLC, authored system requirements/design specifications (SRS/SDS), conducted security vulnerability reviews, and instituted automated integration tests.
Designed and implemented multi-dimensional Star and Snowflake schemas and OLAP cubes for complex analytical querying across multi-gigabyte academic research datasets.
Developed high-performance Python extraction scripts and interactive data visualization prototypes supporting academic publications and research reporting.
Deep dive into the core architectural paradigms engineered across AI, framework infrastructure, and big data systems.
Engineered custom FastMCP (Model Context Protocol) servers to ingest, parse, and structure multi-format Box enterprise data, standardizing AI context retrieval across internal tools and agentic pipelines.
Architected a standardized runtime framework featuring Typer CLI, Alembic database migrations, and dynamic SQL/NoSQL connectors, reducing new data job onboarding time by over 40%.
Architected and automated high-throughput ETL pipelines for global retail business intelligence, optimizing query execution plans to process peak loads of 9M+ records per job with zero pipeline failures.
Academic foundation in Computer Science and Engineering complemented by verified continuous specializations in AI, Cloud, and Data.
Dhaka, Bangladesh
Focused coursework and rigorous foundational training in Algorithms, Distributed Systems, Database Architecture, Object-Oriented Software Design, and Artificial Intelligence.
Verified Professional Credentials
Whether you are architecting an autonomous Agentic AI solution with FastMCP, scaling asynchronous Python microservices, or orchestrating big data pipelines, I'm always open to discussing technical leadership and senior advisory roles.
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Senior Software Engineer with 4+ years of specialized experience architecting enterprise-grade data platforms, distributed backend systems, and Agentic AI architectures. Currently embedded as an Independent Contractor for Apple Inc. within Retail Interactive Technology / DataLab, engineering automated ETL pipelines processing 9M+ records/job with zero pipeline failures, building production FastMCP (Model Context Protocol) servers for enterprise data retrieval, implementing secure vector search with Qdrant and RBAC, and authoring modular Python frameworks (Typer, Alembic) that reduced onboarding cycles by over 40%.
