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AI Product & Engineering Leader | Enterprise GenAI Strategy, Platforms & LLMOps | Business Transformation & ROI | Darden MBA
Innovating at the Intersection of AI and Product Strategy I specialize in building AI-powered products from the ground up, guiding them from concept (0) to launch (1). With a deep understanding of machine learning, AI product management, and enterprise architecture, I combine technical expertise with strategic vision to deliver transformative solutions that drive impact. My passion lies in bridging the gap between cutting-edge AI technologies and real-world applications, ensuring every product is not only innovative but also scalable, user-focused, and aligned with business goals. Whether it’s defining product roadmaps, designing enterprise-level architectures, or driving cross-functional teams toward success, I thrive on turning complex ideas into tangible results. If you’re looking for someone to lead the charge in AI product strategy and development, let’s connect—I’m always eager to collaborate on projects that shape the future of technology.
SBOA School & Junior College
Computer Science
January 1, 2004 – January 1, 2008
University of Virginia Darden School of Business
Master of Business Administration - MBA, Finance, General
N/A – Present
R.M.K Engineering College
Bachelor’s Degree, Electrical and Electronics Engineering
N/A – Present
Strategic Education, Inc
Enterprise Architect - AI
June 1, 2023 – Present
Strategic Education, Inc
Senior Machine Learning Engineer
January 1, 2019 – June 1, 2023
Strategic Education, Inc
Machine Learning Engineer
August 1, 2017 – January 1, 2019
HCL Technologies
Senior Analyst
May 1, 2012 – August 1, 2015
Chennai Area, India
Machine Learning
May 1, 2017 – Present
Developed Python script for classifying authenticity of Bank notes using Deep Learning and Neural Networks techniques with the help of Tensorflow/Skflow Libraries and evaluated the model using traditional machine learning algorithms.
Term Deposit Subscription prediction of Bank clients using Deep Neural Networks
May 1, 2017 – Present
Developed a model in Python to predict if the client will subscribe a term deposit or not using Deep Neural Networks with libraries such as Keras and Tensorflow. The model is trained on over thirty thousand instances and tested on eight thousand instances. The model is also tuned to over 90% accuracy.
Yelp reviews classification using NLP
May 1, 2017 – Present
Developed Python script for analyzing Yelp Reviews, using the dataset from Kaggle and applied machine learning algorithms such as SVM, Naïve Bayes for predictions and NLP text processing.
Logistic Regression Advanced techniques
January 1, 2017 – April 1, 2017
Worked on Kaggle project named House Prices: Advanced Regression Techniques which involves developing regression model with more than eighty factors affecting House price using Python scikit and Pandas, Xgboost.
Predictive Modeling Projects
October 1, 2016 – December 1, 2016
Developed a Multiple Linear Regression model in Python for predicting Stock price with Covariates such as Stock exchanges in the world, Total Competitiveness Weights Index, Lending rate, Opening price, Quarterly and annual reports.
Sentiment Analysis
September 1, 2016 – December 1, 2016
Developed R script for analyzing Presidential Debates 2016, using twitter API, KNN, SVM, Naïve Bayes, NLP and sentimental analysis to identify and categorize opinions expressed in the debate
Generative AI with Large Language Models
Coursera
June 24, 2026 – Present
Neural networks and Deep learning
Coursera
June 24, 2026 – Present
Digital Product management
University of Virginia Darden School of Business
June 24, 2026 – Present
Google Cloud Certified Professional Machine learning engineer
June 24, 2026 – Present
Fine Tune BERT for text classification with TensorFlow
Coursera
June 24, 2026 – Present
Introduction to Machine learning in Production
Coursera
June 24, 2026 – Present
Google Cloud Certified Professional Data Engineer
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from bank note classification to Yelp review analysis and stock price prediction, demonstrates a broad interest in applying ML across different domains. The progression from ML Engineer to Senior ML Engineer and then Enterprise Architect - AI within the same company (Strategic Education, Inc) indicates loyalty and growth, which aligns well with a stable and collaborative culture. The emphasis on EdTech ML products also suggests a mission-driven approach. The MBA background combined with technical roles indicates a blend of business acumen and technical depth, which can be valuable for bridging technical and business teams.
Soft Skills & Operational Fit
The candidate's experience as an Enterprise Architect - AI and Senior Machine Learning Engineer highlights strong leadership, cross-functional collaboration, and strategic thinking. The descriptions indicate an ability to mentor teams, manage product delivery, and report on executive-ready metrics, suggesting good operational fit and communication skills for a senior role. The focus on MLOps and responsible AI also points to a structured and reliable approach to ML system development.