Available for opportunities

Hi, I am

Bogam Abhishek

Gen AI Engineer at Tech Mahindra

Building next-generation Agentic AI systems โ€” from multi-agent RAG pipelines to enterprise LLM orchestration โ€” that solve real-world problems at scale. Passionate about making AI work smarter, not harder.

2+ Years Experience
7+ Certifications
45% Effort Reduction
3 Major Projects
๐Ÿง  Agentic AI
๐Ÿ† Top Performer
โ˜๏ธ Azure Certified
Bogam Abhishek
๐Ÿง  Agentic AI
๐Ÿ† Top Performer
โ˜๏ธ Azure Certified
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01 ยท About Me

The Engineer Behind the AI

Hey! I'm Bogam Abhishek, an Associate Software Engineer at Tech Mahindra, where I work as a Gen AI Engineer building next-generation agentic AI systems that drive real enterprise impact.

My focus is on LLM orchestration, Agentic RAG architectures, and multi-agent systems โ€” intelligent pipelines that don't just retrieve information, but reason, plan, and act on it.

I've delivered systems reducing manual effort by 45%, cutting API costs by 25%, and improving query accuracy by 30% โ€” all in production telecom environments.

  • ๐Ÿ“ Andhra Pradesh, India
  • ๐Ÿ’ผ Associate Software Engineer @ Tech Mahindra
  • ๐ŸŽ“ B.Tech CS โ€” MITS (GPA: 8.42/10)
  • ๐Ÿ“ง
Get In Touch โ†’
๐Ÿง 

Agentic AI

Multi-agent RAG with planning, reasoning, and sub-query decomposition.

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LLM Infra

On-prem & hybrid deployment using vLLM, OpenVINO, Groq and HuggingFace.

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Award Winning

3rd place @ Microsoft ร— TechM Ideathon. Awarded @ Microsoft Agentic AI Hackathon.

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Cloud Native

Azure-certified. Deployed production AI systems on Azure in rapid 4-day cycles.

02 ยท Experience

Where I've Made Impact

Production-grade AI systems for real enterprise challenges.

Tech Mahindra ASD March 2024 โ€“ Present
Associate Software Engineer ยท Gen AI Engineer

  • โ†’ Developed and deployed an Agentic RAG system for automated 4G/5G (3GPP) test case generation, reducing manual effort by 45%.
  • โ†’ Designed multi-step reasoning workflows using planning-based task decomposition, improving complex telecom query accuracy by 30%.
  • โ†’ Implemented domain-specific embedding segmentation (AMF, SMF, Core Network) with intelligent retrieval routing, reducing latency by 35% and improving semantic relevance.
  • โ†’ Engineered a scalable Flask backend integrating on-prem LLM inference (vLLM, OpenVINO) and hybrid API models (Hugging Face, Groq), enabling multi-model orchestration and concurrent inference.
  • โ†’ Optimized modular RAG pipelines for enterprise deployment, reducing token consumption and API cost by 25%.
45% Effort Saved
30% Query Accuracy
35% Latency Reduced
25% Cost Reduction
03 ยท Skills

Tools of the Trade

Technologies I use to build intelligent, production-grade AI systems.

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Languages
Python JavaScript HTML CSS
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Frameworks & Backend
Flask FastAPI
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AI / LLM Frameworks
LangChain LangGraph RAG Multi-Agent MCP
๐Ÿ—„๏ธ
Vector Databases
FAISS Azure AI Search
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LLM Inference & APIs
vLLM OpenVINO Groq Google API HuggingFace
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Tools & Design
Git Figma Adobe PS Azure
04 ยท Projects

Things I've Built

Production-ready AI systems tackling real-world enterprise challenges.

01
RAG Production
TrustRAG

A source-aware, memory-enabled RAG system built with FastAPI, FAISS, and LLaMA-3 via Groq for grounded responses on large technical documents. Retrieval-first architecture with domain-aware controls to enhance accuracy and minimize hallucinations.

FastAPI FAISS LLaMA-3 Groq Python
02
AI Azure FinTech
AI Financial Credibility Analyser

Production-ready AI system for automated KYC validation and financial risk assessment using Flask, Azure Blob Storage, and Azure AI Document Intelligence. Integrated hybrid vector retrieval with Azure AI Search and Azure OpenAI to generate structured PDF credibility reports โ€” deployed on Azure in just 4 days.

Flask Azure Blob Azure OpenAI Azure AI Search
03
Multi-Agent Architecture
AgenticRAG Orchestrator

Multi-agent RAG system with clustered topic-based embedding generation, Sub-Query Decomposition Agent, and intelligent retrieval routing for improved semantic precision and multi-hop reasoning across complex, distributed knowledge bases.

LangGraph LangChain Multi-Agent FAISS Python
05 ยท Awards

Recognition & Achievements

Honored for technical excellence and innovative AI delivery.

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Top Performance Rating โ€” Two Consecutive Years

Received Top Performance rating for two consecutive years at Tech Mahindra for outstanding technical delivery in Gen AI engineering.

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3rd Place โ€” Microsoft ร— Tech Mahindra Ideathon

Secured 3rd place among 80+ teams for presenting an Agentic RAG model demonstrating real-world enterprise applicability.

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Microsoft Agentic AI Hackathon Award

Awarded at the Microsoft Agentic AI Hackathon for developing a multi-agent solution using the AutoGen framework.

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Pat on Back Award โ€” Tech Mahindra

Recognized for exceptional contributions and going above and beyond the scope of assigned technical deliverables.

06 ยท Certifications

Certified Expertise

Industry-recognized credentials across cloud, AI, and development.

07 ยท Education

Academic Foundation

B.Tech ยท May 2023
Computer Science Engineering
Madanapalle Institute of Technology & Science
Andhra Pradesh, India
โญ GPA: 8.42 / 10.0
Intermediate ยท May 2019
Intermediate Education (MPC)
Bharathi Junior College
Andhra Pradesh, India
โญ GPA: 8.03 / 10.0
SSC ยท May 2017
Secondary School Certificate
Ravindra Bharathi School
Andhra Pradesh, India
โญ GPA: 8.3 / 10.0
08 ยท Contact

Let's Build Something Great

I'm open to exciting Gen AI opportunities, collaborations, and conversations about agentic systems, LLM architectures, or anything at the frontier of AI. Don't hesitate to reach out โ€” I'd love to connect.

Send a Message

I typically respond within 24 hours.

Bogam Abhishek
Resume / CV