Browse categories
Explore
Fiverr Pro
English
$
USD
I will build langchain multi agent architectures for your data workflows
Arpit Pati
About this gig
Stop relying on manual scripting for tedious data engineering. As a Google Cloud Certified Data Engineer specializing in AI architectures, I bridge the gap between complex data ecosystems and state-of-the-art LLMs.
I architect custom, autonomous multi-agent systems using LangChain and the Model Context Protocol (MCP) to automate heavy workflowsfrom intelligent schema mapping to translating legacy PL/SQL into performant BigQuery syntax.
What I Can Do For You:
- Multi-Agent Systems: Orchestrate specialized LLM agents to collaborate on complex data tasks.
- Smart Code Translation: Automate legacy SQL-to-cloud migration with high precision.
- Context-Aware AI: Implement MCP and vector databases so LLMs securely understand your proprietary schemas.
- Enterprise Security: Use enterprise APIs (Vertex AI) to ensure logic never leaks to public models.
Tech Stack: LangChain, Python, MCP, Vertex AI/OpenAI, GCP, BigQuery, Vector DBs.
Why Choose Me? I don't build generic chatbots; I build secure data pipelines. You get a certified architect who applies AI to solve real data bottlenecks.
Please message me before ordering!
Get to know Arpit Pati
Arpit Pati
- FromIndia
- Member sinceOct 2022
Languages
English, Hindi
I’m Arpit, an IIT M.Tech graduate and GCP Certified Data Engineer specializing in architecting high-impact, scalable solutions. With 4+ years of expertise across data engineering, full-stack development, and published AI research (AII London 2024 and ICICV 2025), I transform complex technical challenges into enterprise-grade performance. From building autonomous LLM multi-agent systems to optimizing financial cloud pipelines, I bring a blend of academic rigor and hands-on engineering excellence to your project. Ready to scale your vision? Let’s connect and build your next-gen tech stack.
FAQ
Are my databases and proprietary code secure?
Absolute security is the foundation of my architecture. We utilize enterprise-tier APIs directly within your cloud environment. Your proprietary data and schemas are strictly isolated and never used to train public models.
What is the Model Context Protocol (MCP) and why do I need it?
MCP is a standardized way for AI agents to connect securely to your existing data sources. It allows the LLM to understand your database context and execute queries directly, turning a generic AI into a highly specialized data assistant.
Which LLMs do you use for these agents?
I am model-agnostic and adapt to your ecosystem. For GCP-heavy environments, I utilize Vertex AI (Gemini). I am also highly proficient in building LangChain architectures around OpenAI's GPT-4 or Anthropic's Claude.
Can these agents fully replace manual data migration?
AI agents drastically accelerate the process, handling 80-90% of the heavy lifting. However, complex edge cases still require expert review, which I integrate into the pipeline workflow.
