---
title: "Shreyas B. - Software Engineer in Bengaluru | Tal"
description: "Meet Shreyas B., Software Engineer @ ABB | LLMOps, Data Science, AI Engineering based in Bengaluru. AI stack includes langchain, langfuse, and langgraph. Explore public work links including github."
image: "https://tal.club/meet/shreyas-bhat/share-image"
---

# Shreyas B\. on Tal

## Headline

Software Engineer @ ABB \| LLMOps, Data Science, AI Engineering

## About

As a Software Engineer at ABB, I contribute to the development of Agentic LLM application like ABB Genix Copilot\. Leveraging expertise in LLMOps, I design, deploy, and optimize agentic applications, utilizing tools like Langfuse, Langgraph, Azure Kubernetes Service, and Azure DevOps for scalable and reliable cloud\-native deployment\. Projects I contributed to \(ABB Genix Copilot\) https://new\.abb\.com/process\-automation/genix/abb\-genix\-copilot https://news\.microsoft\.com/source/emea/2026/04/abb\-enhances\-ai\-capabilities\-of\-flagship\-industrial\-device\-digital\-solutions/

## Location

Bengaluru

## AI stack

langchain

langfuse

langgraph

langsmith

mcp

openai

## Work experience

Software Engineer at ABB, Aug 2024 \- Present · 2 yrs 2 mos, Hybrid, • Worked on Genix Copilot, an agentic LLM system, where I developed and managed core modules including Text\-to\-MongoDB query generation, Document QA, Agent orchestration Flow, and evaluation pipelines\. • Implemented advanced retrieval \+ re\-ranking strategies for RAG, improving retrieval quality and increasing groundedness by 27% and completion accuracy by 40% on test dataset\. • Managed containerized deployments on Azure Kubernetes Service using Azure DevOps CI/CD for continuous delivery across different environments • Built end\-to\-end Agent Observability using Langfuse and custom telemetry to monitor agent performance, track key metrics, and drive continuous optimization\. • Developed an MCP server layer over existing backend services, enabling standardized integration between enterprise capabilities and the agent\. • Official product article: https://new\.abb\.com/news/detail/124533/abb simplifies\-industrial\-device\-maintenance\-with\-generative\-ai

Software Engineer Intern \(Full Stack\), ABB at ABB, Jan 2024 \- Aug 2024 · 8 mos, On\-site, • Built a full\-stack ML sensitivity analysis platform using Angular, TypeScript, Reactive Forms, and RxJS for dataset uploads, scenario configuration, and real\-time metric visualization\. • Developed asynchronous FastAPI services with multiprocessing for parallel inference across perturbed datasets, reducing experiment setup time by 50%\. • Automated model robustness evaluation and before/after performance comparisons, reducing manual validation effort by 60%\. • Containerized and deployed the platform on AKS using Docker, Helm, ingress controllers, and horizontal pod autoscaling for scalable inference workloads\.

Data Science Intern at Exponentia\.ai, Jun 2023 \- Sep 2023 · 4 mos, Mumbai, Maharashtra, India, • Created an innovative application that utilizes open\-source Large Language Models to produce concise document summaries\. • Designed an chat\-bot powered by an open\-source Large Language Models, enabling seamless interaction with unstructured data for precise information retrieval from a database, tailored to user queries\.

Data Engineer at ESG Data &amp; Solutions, Dec 2022 \- Mar 2023 · 4 mos, Remote, • Developed data preprocessing pipelines to ensure data integrity, normalization, and readiness for analytical workflows\. • Utilized Power BI to design and deploy interactive dashboards and visualizations, enabling dynamic exploration of financial datasets and enhancing stakeholder decision\-making processes\. • Applied additional Python packages such as Matplotlib, Seaborn, and Plotly to generate detailed visual analytics and uncover underlying trends in ESG financial data\.

Senior Member at Project MANAS, May 2021 \- May 2023 · 2 yrs 1 mo, Manipal, • Developed a machine\-learning model using motor telemetry and flight\-path parameters to predict UAV energy consumption, optimize battery selection, and balance aircraft weight against flight endurance\. • Successfully executed Static and Dynamic simulations of the UAV using MATLAB and Ansys, alongside conducting on\-field testing for real\-world validation\. • Contributed to end\-to\-end autonomous UAV development with multi, including sensor\-data processing, flight simulation, mission planning, software integration, and mission execution for the AUVSI SUAS 2022 competition\. Accomplishments: • Secured 2nd position in Flight Readiness Review, demonstrating the comprehensive development process of the drone\. • Attained 10th position in the Technical Design paper and an overall ranking of 18th out of 71 teams from various countries in a global competition\. • Achieved an overall ranking of 18th in the AUVSI SUAS International autonomous drone competition\. Competition Ranking: https://docs\.google\.com/spreadsheets/d/e/2PACX\-1vSV0\_wulZ\_djNrAeuGUOWQXyDoUyD6lgD5H7W9tqT8LZu\_\_uv6s0OiEsDP0lbRetUTWTqQ9S1RAdvAr/pubhtml \(year 2022\)

## Education

Bachelor of Technology \- BTech, Data Science, Manipal institute of technology

Bombay Cambridge International School, Andheri East

## Public links

- github: https://github\.com/Shreyas\-gits

[View the original profile](https://tal.club/meet/shreyas-bhat)

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