Lead Software Engineer at Capital One | AWS | AI/ML | Big Data/Spark
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I have extensive experience of software development and leading teams from startups to some of the largest organizations in the world. I have extensive hands-on experience in the area of Machine Learning, Deep Learning, Big Data, Apache Hadoop, Hive, Apache Spark, Python, Java, C/C++, Scala, Flask/Django frameworks. I am certified developer in Java, Apache Spark, and Machine Learning with specialization in Deep Learning.
Motilal Nehru National Institute Of Technology
BE, Comp Sc
January 1, 1994 – January 1, 1998
Capital One
Lead Software Engineer
March 1, 2019 – Present
Wilmington, Delaware, United States
JPMorgan Chase & Co.
Vice President: Big Data (Spark, Python, ML) Analytics
July 1, 2017 – September 1, 2018
Newark, DE
Impetus technology - American Express
Big Data Lead Developer
April 1, 2016 – July 1, 2017
Greater Phoenix Area
Visa
Hadoop Lead Developer Consultant
January 1, 2016 – March 1, 2016
San Francisco Bay Area
Qualcomm
Staff Engineer (Big Data, Android)
July 1, 2013 – December 1, 2015
San Diego, CA
Avaya
Techinal Lead
December 1, 2009 – June 1, 2013
Santa Clara, CA
Nortel Networks
Sr Software Engineer
July 1, 2007 – November 1, 2009
Santa Clara, CA
Tech Mahindra
Design lead
January 1, 2005 – January 1, 2007
Bangalore, India
Axes Technologies (I) Pvt Ltd
Sr Software Engineer
January 1, 2001 – January 1, 2005
Bangalore, India
BEL Kotdwara
Software Engineer
September 1, 1998 – March 1, 2001
Kotdwara, India
Introduction to AI and Machine Learning on Google Cloud
Google Cloud
June 24, 2026 – Present
Getting Started with AWS Generative AI for Developers
Amazon Web Services
June 24, 2026 – Present
Generative AI for Everyone
Coursera
June 24, 2026 – Present
Using TensorFlow with Amazon Sagemaker
Coursera
June 24, 2026 – Present
Trading Basics
Coursera
June 24, 2026 – Present
Advanced Trading Algorithms
Coursera
June 24, 2026 – Present
Python and Statistics for Financial Analysis
Coursera
June 24, 2026 – Present
Big Data Foundations
IBM
June 24, 2026 – Present
Hadoop Platform and Application Framework
Coursera Course Certificates
June 24, 2026 – Present
Introduction to Big Data by University of California, San Diego
Coursera Course Certificates
June 24, 2026 – Present
Oracle Certified Associate, Java SE 7 Programmer
Oracle
June 24, 2026 – Present
Computational Investing, Part I
Coursera
June 24, 2026 – Present
Fundamentals of Building AI Agents
IBM
June 24, 2026 – Present
Generative AI Applications with Amazon Bedrock
Amazon Web Services
June 24, 2026 – Present
The Science of Well-Being
Coursera
June 24, 2026 – Present
Getting started with Flutter Development
Coursera
June 24, 2026 – Present
Machine Learning for Trading Specialization
Coursera
June 24, 2026 – Present
Machine Learning with Python
Coursera
June 24, 2026 – Present
Data Visualization with Python
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Machine Learning With Big Data
Coursera Course Certificates
June 24, 2026 – Present
An Introduction to Interactive Programming in Python
Coursera
June 24, 2026 – Present
Pattern-Oriented Software Architectures: Programming Mobile Services for Android Handheld Systems
Coursera
June 24, 2026 – Present
AWS Generative AI and AI Agents with Amazon Bedrock Specialization
Amazon Web Services
June 24, 2026 – Present
Amazon Bedrock Customization, Optimization & Automation
Amazon Web Services
June 24, 2026 – Present
Team Software Engineering with AI
Coursera
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
Using Machine Learning in Trading and Finance
Coursera
June 24, 2026 – Present
Introduction to Trading, Machine Learning & GCP
Coursera
June 24, 2026 – Present
Trading Algorithms
Coursera
June 24, 2026 – Present
Big Data Hadoop Foundations
IBM
June 24, 2026 – Present
Data Analysis with Python
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI
IBM
June 24, 2026 – Present
Agentic AI with LangChain and LangGraph
IBM
June 24, 2026 – Present
Introduction to Generative AI for Software Development
Coursera
June 24, 2026 – Present
AWS Certified Machine Learning – Specialty
Amazon Web Services (AWS)
June 24, 2026 – Present
Reinforcement Learning for Trading Strategies
Coursera
June 24, 2026 – Present
AWS Certified Solutions Architect - Associate
Amazon Web Services (AWS)
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
MapR Certified Spark Developer 1.6 (MCSD)
MapR Technologies, acquired by Hewlett Packard Enterprise company in 2019
June 24, 2026 – Present
Introduction to Big Data Analytics
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong commitment to continuous learning and adapting to new technologies, particularly in the Big Data and AI/ML space. The breadth of certifications, from foundational Big Data to advanced Generative AI and AWS ML, indicates a proactive approach to skill development. The experience across various large enterprises (Capital One, JPMorgan Chase, Qualcomm, Visa) suggests an ability to work within structured environments. However, the lack of detailed project descriptions makes it challenging to assess alignment with specific team cultures or innovative project approaches. The target role of ML Engineer aligns well with the recent focus on AI/ML certifications.
Soft Skills & Operational Fit
The candidate's extensive career progression through various lead and senior roles suggests strong leadership, problem-solving, and operational capabilities. The numerous certifications in cutting-edge AI/ML topics indicate a proactive and continuous learning mindset, which is crucial for adapting to evolving technologies in an ML Engineer role. However, without specific project details or behavioral assessment data, it is difficult to fully assess soft skills like collaboration, adaptability, and communication in a practical work setting.