Summary
Overview
Work History
Education
Skills
Timeline
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Anmol Kumar

Bengaluru

Summary

Associate Product Developer with expertise in BMC Adapt-Angular, FastAPI, and RAG-based systems. Proven track record in delivering enhanced UI components and AI-driven applications

Overview

3
3
years of professional experience

Work History

Associate Product Developer

BMC Software
Bangalore
07.2022 - Current
  • Built and enhanced UI panels using the BMC Adapt Angular framework, including implementing Adapt tables (covering approximately 80% of the product structure) and enabling lazy loading across the IMS Command Center, which significantly improved performance. Recognized and appreciated by product managers and senior leadership for these contributions.
  • Created an intuitive, modern JCL editor web component with real-time error detection and advanced features, soon to be released as an npm package under bmc-des for wider use. Appreciated by senior developers and the manager.
  • Developed a RAG-based application using FastAPI, integrating vector databases like FAISS, with LangChain and LangGraph, to deliver accurate, domain-specific responses.
  • Added a GPT-style chat interface within the IMS Command Center using Adapt Angular, integrated with RAG pipelines, and tool-calling for Agentic Flow, enabling the system to retrieve live IMS data. Presented to product line operations, and the prototype is moving toward full product integration.
  • Created an AI-driven analysis feature for IMS Message Advisor queues by retrieving real-time data from the mainframe via PCH/UIM APIs, combining multiple system prompts with RAG strategies. It is also moving forward with product line operations.
  • Explored and implemented multiple chunking strategies for RAG during a Root Cause Analysis hackathon, building an interactive dashboard to demonstrate the workflow. Conducted demos and knowledge-sharing sessions with product teams, and it is moving toward full product integration.
  • Designed and built RAGMaster, a reusable project that allows users to query their own document collections with full RAG and Self-RAG support, backed by detailed documentation and algorithms.
    Authored a research paper on agentic AI and RAG implementations in enterprise systems, outlining technical details, architectural approaches, and a complete implementation guide.
  • Pre-trained custom small language models (15M and 20M parameters) with a 256-token context window on an NVIDIA RTX 3070 Ti (8GB), inspired by OpenAI’s TinyStories research. Completed 3-epoch training in approximately 13 hours, capable of generating coherent short stories.
  • I developed an NLP-powered chatbot during my final-year internship at Celebal Technologies, using TensorFlow for a client project.
  • Awarded a Gold Medal in IBM ICE for a project on creating VSAM and GDG datasets through Jenkins pipelines.

Education

Bachelor of Science - Computer Science

University of Petroleum And Energy Studies
Dehradun
03-2022

Skills

  • BMC Adapt-Angular framework
  • FastAPI development
  • Natural language processing
  • RAG-based systems
  • Python, PyTorch, and TensorFlow
  • Custom AI model training
  • Agentic AI
  • LangChain and LangGraph

Timeline

Associate Product Developer

BMC Software
07.2022 - Current

Bachelor of Science - Computer Science

University of Petroleum And Energy Studies

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Anmol Kumar