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Senior Director of Engineering @ Experian | AI/ML & Real-Time Data Platforms | 10M QPS | Built Platform to Acquisition
Technical executive who builds high-performance AI and data platforms from zero to scale. Led engineering for real-time identity resolution platform from inception through Experian acquisition—now processing 10M queries/second at sub-4ms latency across 1 trillion+ daily events. My focus: architecting AI/ML-powered systems where milliseconds and scale matter. Built RTDP in Go, achieving performance metrics that required going beyond conventional cloud architectures. Led technical due diligence that drove a strategic acquisition. 10+ years in adtech and data intelligence. Deep expertise in real-time ML systems, identity resolution, and distributed infrastructure. I thrive where technical depth—actually building things from scratch—matters as much as team leadership. Currently driving AI strategy and post-acquisition integration at Experian, scaling identity resolution and data curation products for Fortune 500 clients globally.
University of California, Riverside
Masters, Computer Science
N/A – Present
Visvesvaraya Technological University
Bachelor of Engineering (B.E.), Computer Science
N/A – Present
Experian
Senior Director of Engineering
April 1, 2025 – Present
New York, New York, United States · On-site
Audigent
Chief Engineer
February 1, 2022 – March 1, 2025
New York City Metropolitan Area · On-site
Digilant
VP of Technology
April 1, 2020 – February 1, 2022
Digilant
Director of Engineering & Machine Learning
April 1, 2016 – April 1, 2020
Digilant
Data Scientist
July 1, 2014 – March 1, 2016
Digilant
Data Engineer
October 1, 2013 – June 1, 2014
University of California, Riverside
Teaching Assistant
April 1, 2013 – June 1, 2013
University of California, Riverside
Teaching Assistant
April 1, 2012 – December 1, 2012
University of California, Riverside
System Admin LATTE LAB
October 1, 2011 – March 1, 2012
Masters Capstone Project: Unified Geo-Replicated Storage Service
January 1, 2013 – August 1, 2013
Designed an internet scale object store (similar to Amazon S3) with automatic replication over multiple data centers around the world. Runs on top of multiple cloud services like Amazon AWS, Google Cloud Platform and Microsoft Azure and provides a single unified interface to application developers using the storage service. The automatic replication and a single interface provide a global view of storage that the application developer can make use of to provide low latency service to end users. Intelligently reduces the costs by taking advantage of pricing differences between different regions and cloud services. Validated the prototype performance by porting two real word applications: retwis, a clone of twitter and sharejs a document collaboration service to use my system as back end storage.
Highly Parallel Frequent item Set Mining using GPU’s
March 1, 2012 – Present
Implemented Apriori algorithm, to leverage the highly parallel architecture of modern GPU’s using Nvidia’s CUDA SDK.
Dynamic Bandwidth Limiting Tool For XEN Hypervisor
February 1, 2011 – June 1, 2011
Designed and developed a dynamic bandwidth limiting tool that works with the XEN Hypervisor to manage network bandwidth assigned to different virtual machines running on the same physical server.
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Tackling the Challenges of Big Data
Massachusetts Institute of Technology
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in ad-tech and data-intensive environments, which suggests a good fit for fast-paced, data-driven cultures. Their experience in building teams from scratch and leading post-acquisition integrations indicates adaptability and a proactive approach to organizational change. The project diversity, from GPU-based mining to geo-replicated storage, shows a broad technical curiosity and willingness to tackle complex challenges, aligning with an innovative culture. However, the target role of 'Data Analyst' might be a step down from their current 'Senior Director of Engineering' role, potentially indicating a mismatch in career aspirations or a desire for a more hands-on technical role. This could be a point to explore for cultural fit.
Soft Skills & Operational Fit
The candidate's career progression from Data Engineer to Senior Director of Engineering demonstrates strong leadership, team building, and strategic thinking. Their experience in leading cross-functional teams and driving technical strategy for AI/ML roadmaps indicates excellent operational fit and ability to manage complex projects. The descriptions highlight problem-solving and impact-driven approaches.