class AniketSinhaRoy:
def __init__(self):
self.role = "Python Developer"
self.location = "India ๐ฎ๐ณ"
self.focus = ["Agentic AI", "Generative AI", "Data Engineering"]
self.learning = ["LangGraph", "MCP (Model Context Protocol)", "Agentic Workflows"]
self.contact = "aniketsinharoy@gmail.com"
self.fun_fact = "My servers have 99.9% uptime. My AI agents are self-healing. I run on chai, and I crash daily."
def current_stack(self):
return {
"AI/ML" : ["LangChain", "LangGraph", "MCP", "Generative AI"],
"Data" : ["PySpark", "Pandas", "Tableau", "SAP BO"],
"Backend": ["Python", "MySQL", "MongoDB", "Oracle"],
"DevOps" : ["Linux", "Unix", "Git", "Bitbucket", "GitHub"],
"OS" : ["Linux", "Unix", "Windows"],
}| Layer | Technologies |
|---|---|
| ๐ค Agentic AI | LangGraph ยท MCP (Model Context Protocol) |
| ๐ LLM Orchestration | LangChain ยท Prompt Engineering |
| ๐ Data & Analytics | PySpark ยท Pandas ยท Tableau ยท SAP BO |
| ๐๏ธ Databases | MySQL ยท MongoDB ยท Oracle |
| ๐ฅ๏ธ Systems | Linux ยท Unix ยท Windows |
| ๐ง Dev Tools | Git ยท GitHub ยท Bitbucket ยท Postman ยท MS Office |
๐ญ Building Agentic AI workflows using LangGraph & MCP
๐ฑ Exploring multi-agent orchestration and tool-use patterns
๐ Delivering insights through Tableau & SAP BO dashboards

