Principal AI Architect | Agentic AI · RAG · LLMOps | Ex-CTO
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Principal AI Architect & Ex-CTO with a decade of experience engineering scalable ML products, from raising $3M in venture capital to architecting GenAI ecosystems for Google Cloud. Expert in designing high-concurrency Agentic Workflows, RAG architectures, and LLMOps pipelines that drive multi-million dollar operational savings. Proven track record of leading cross-functional teams to deliver production-grade AI solutions with sub-second latencies and enterprise-grade governance.
Guru Ghasidas University
Bachelor of Technology (Honours), Computer Science and Engineering
January 1, 2014 – January 1, 2018
Relanto
Principal Data Scientist
May 1, 2025 – Present
Bengaluru · Hybrid
Applied Materials
Senior AI Architect
September 1, 2023 – March 1, 2025
Bangalore Urban · Hybrid
XA Group
AI Architect
December 1, 2021 – April 1, 2023
Bangalore Urban, Karnataka, India
upGrad
Machine Learning Coach
August 1, 2019 – August 1, 2022
India
Agrograde
CTO
April 1, 2019 – July 1, 2021
Navi Mumbai
Agrograde
Data Scientist
May 1, 2018 – December 1, 2019
Navi Mumbai
AgricxLab
Intern in Computer Vision And Machine Learning
May 1, 2017 – January 1, 2018
Mumbai Area, India
Udaan Hindi
Editor In Chief
May 1, 2015 – May 1, 2017
Chhattisgarh, India
AI pipeline for image forensic
April 1, 2023 – June 1, 2023
Client - Linksmart Service - Custom AI pipeline for counterfeit detection in labeling.
Defect Detection in Solar Cells
January 1, 2023 – May 1, 2023
Client - DataKalp Service - Automatic defect detection and classification in solar cells using EL-Imaging and computer vision
Vehicle Damage Assessment Platform
December 1, 2021 – January 1, 2023
Working with XA group to deliver automatic damage detection pipeline. The scope of the project includes dataset pipelines, modeling, ML CI/CD, and an all-encompassing self-training pipeline (domain-specific).
Task Agnostic Pre-training
April 1, 2021 – June 1, 2021
Implementation of simCLR paper. Used the LARS optimizer over the contrastive loss function as described in the paper to train a contrastive model. Used this model as an encoder and added a fully connected layer to create a classifier.
Optical Sorting Based on Deep Learning
May 1, 2019 – July 1, 2020
The main aim of this project was to utilize the power of deep learning in damage detection and sorting of agricultural produce. It was an end-to-end product involving computer science as well as mechanical design. I contributed as a Data Scientist and System Designer. Utilized ROS to design and create the backend of the machine. One of the main achievements as a team was to port the performance of heavier models that needed GPU to much, much smaller models that would run on CPU.
Video Analytics
April 1, 2018 – June 1, 2018
Computer Vision based video analysis including but not limited to tracking, speed detection, crowd detection, tailgating etc.
Speech Detection using CNN
February 1, 2018 – March 1, 2018
An attempt to identify words from spectrogram using Fast Furrier Transformation as feature descriptor and CNN as classifier.
Iceberg Detection from satellite data
January 1, 2018 – February 1, 2018
The dataset was provided by kaggle.com. With the help of image augmentation and CNN, I managed to classify the iceberg from ships and islands present in the form of spectral data.
Grading and Disease Detection in Potatoes
October 1, 2017 – April 1, 2018
Applied the current deep learning techniques in detection and segmentation of each potato from images which usually contained 100-150 potatoes. Further we scaled them in centimetres and gained insight about the size distribution of the objects. Refer to the publications section.
Ultrasound nerve segmentation using AutoEncoders
January 1, 2017 – March 1, 2018
The data set contained images and the mask associated with them. Trained U-Net architecture for segmentation of nerves.
Programming Foundations: Secure Coding
June 23, 2026 – Present
Application Security in DevSecOps
June 23, 2026 – Present
Ten Security Tips for Developers
June 23, 2026 – Present
Introduction to Computer Vision by GorgiaTech
Udacity
June 23, 2026 – Present
Convolutional Neural Networks by deeplearning.ai on Coursera
Coursera
June 23, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 23, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 23, 2026 – Present
The Analytics Edge
edX
June 23, 2026 – Present
Certification for data analysis in R
Coursera
June 23, 2026 – Present
NetTech Certification of Network Engg
NetTech
June 23, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from agricultural tech startups to large enterprises like Applied Materials, suggests adaptability and a broad interest in applying AI across different domains. Their experience in both hands-on development and leadership roles indicates a versatile profile. The long tenure at Agrograde (Data Scientist to CTO) shows commitment and growth within an organization. The freelance coaching role indicates a willingness to share knowledge and contribute to the community.
Soft Skills & Operational Fit
The candidate's experience as a Principal Data Scientist and Senior AI Architect indicates strong leadership, project management, and problem-solving skills. Their role as an ML Coach also suggests good communication and mentoring abilities. The descriptions highlight a focus on delivering business value and operational efficiency through AI solutions.