> Kamruzzman Shuvo | Independent Contractor for Apple Inc.
Architecting autonomous systems using Claude Code, Model Context Protocol (MCP), and enterprise-grade Python frameworks. Proven track record in orchestrating high-performance backend pipelines, distributed ETLs, and cloud microservices.
# FastMCP Autonomous Skill Integration for Apple RIT
from fastmcp import FastMCP, Context
from pydantic import BaseModel, Field
from core.claude_code import PluginExecutor
mcp = FastMCP("Apple-RIT-Autonomous-Engine")
@mcp.tool()
async def orchestrate_retail_flow(
store_id: str,
intent: str,
ctx: Context
) -> dict:
"""Trigger digital-physical retail interaction workflow."""
ctx.info(f"Synthesizing RIT telemetry for store {store_id}")
return await PluginExecutor.run(intent, fast_sync=True)
Specialized in bridging high-level LLM reasoning with deterministic enterprise backend infrastructure.
Senior Software Engineer & AI Architect
As a Senior Software Engineer at Softzino Technologies working as an independent contractor for Apple Inc., I architect autonomous Agentic AI systems, custom AI skills, and resilient backend pipelines for digital-physical environments.
My engineering focus centers on Model Context Protocol (MCP), Claude Code plugins, and asynchronous Python architectures (FastAPI, Pydantic, SQLAlchemy) that handle mission-critical workload automation with zero downtime.
With a strong foundational background in data warehousing (Star/Snowflake schemas, OLAP) and distributed computing, I design frameworks that standardize script execution, database orchestration, and cloud deployments across enterprise microservices.
From cutting-edge autonomous Agentic AI tooling to distributed database architectures and cloud infrastructure.
Architecting autonomous agents, MCP protocol servers, RAG pipelines, and Claude Code skills.
High-throughput async APIs, ORM management, strict typing, task queues, and CLI tooling.
Massive dataset ingestion, multidimensional dimensional modeling, OLAP analytics, and warehouse readiness.
Container orchestration, continuous delivery pipelines, serverless workflows, and gateway tuning.
Demonstrated history of driving impactful engineering at industry-leading organizations.
Led technical operations for the Virtual Internship System; mentored 50+ interns in Data Analytics and software fundamentals.
Spearheaded the full SDLC from SRS/SDS architectural design to security vulnerability auditing for core platforms.
Optimized legacy backend modules, significantly enhancing throughput and query speeds for health data analytics and platform reporting.
Developed Big Data analytics solutions featuring multidimensional Star and Snowflake schema modeling and high-performance OLAP processing.
Built high-performance software prototypes for academic research, focusing on high-volume data visualization, aggregation algorithms, and real-time dashboarding.
Deep dive into the core architectural paradigms engineered across AI, framework infrastructure, and big data systems.
Engineered autonomous Agentic AI workflows using FastMCP and custom Claude Code plugins for Apple RIT. Bridges real-world physical retail interactions with digital intelligence through deterministic tool-calling and context orchestration.
Engineered a standardized runtime platform that enables teams to deploy arbitrary Python scripts into production in minutes. Built-in zero-downtime database migration hooks, multi-engine persistence, and dual CLI/REST interfaces.
Orchestrated automated data pipelines for the Global Business Intelligence Data Lab, transforming unstructured high-velocity data into clean star/snowflake dimensional schemas for enterprise analytics and executive reporting.
Academic foundation, verified industry specializations, and professional references.
Dhaka, Bangladesh • 2017 – 2020
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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