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Kuber Raj Kunal

@kuberrajkunal

Agentic AI Engineer at Capgemini building Google Cloud multi-agent platforms, including one that improved pipeline reliability by 40%.

India

Message

At Capgemini, I architected an enterprise multi-agent platform using Google ADK 2.x graph workflows and GCP, improving pipeline reliability by 40%. I also built FastAPI and React orchestration with human-in-the-loop guardrails and developed workflows that reduced manual data preparation effort by 60%.

Previously at Capgemini, I engineered a GenAI accelerator to automate migration of legacy Teradata SQL files to BigQuery. I also built the Automated Agentic RAG Framework, a grounded Gemini-powered assistant with document-triggered embedding updates, SSE streaming, and a Python backend.

Experience

Work history, roles, and key accomplishments

Current

Agentic AI Engineer

Current

Capgemini

Jan 2026 - Present (9 months)

Architected an enterprise multi-agent platform using Google ADK 2.x graph workflows and GCP, boosting pipeline reliability by 40%. Built full-stack orchestration with FastAPI and React, and developed multi-agent workflows using FastMCP and Pydantic schemas.

Google ADK GCP fastAPI React FastMCP Pydantic Docker Cloud Run Human In The Loop Multi agent orchestration

Senior Analyst

Capgemini

Oct 2024 - Dec 2025 (1 year 2 months)

Engineered a high-availability GenAI accelerator to automate migration of thousands of legacy Teradata SQL files to BigQuery. Applied iterative prompt tuning to maximize SQL translation accuracy, reducing manual conversion hours by 65%.

GenAI GCP BigQuery Teradata SQL Python React Prompt Engineering

AI Engineer

Personal Project

Architected a zero-infrastructure RAG assistant using GitHub Actions to automatically re-generate semantic embedding JSON files on document commits. Deployed a grounded Gemini-powered agent featuring SSE streaming, with a Python backend on Render and a React/Tailwind frontend on Vercel.