Experience

McDonald’s Corporation

Manager, Engineering Tech Lead

Sept 1st 2025 - Present
Chicago, Illinois

• Leading Technical & People Excellence: Leading 6 engineers while driving architecture, design reviews, technical risk management, production operations. Fostering continuous improvement and advocating for the responsible use of emerging AI engineering tools to enhance productivity, innovation, and engineering quality.
• Driving Global Scale & Reliability: Own the end-to-end delivery of C#/.NET backend services supporting 55+ markets, leveraging RESTful APIs, microservices architecture, NoSQL DBs, Kafka to deliver reliable, scalable solutions.
• Delivering High-Impact Global Launches: Led 6 major launches across global markets, partnering with product, engineering, legal, and local teams on tax, regulatory, compliance, production readiness, and operational stability.

Software Engineer 2

Oct 1st 2023 - Aug 31st 2025
Chicago, Illinois

• Pioneering Software Launches – Spearheading software feature development, defect resolution, and deployments, ensuring seamless digital ordering launches in major and lite markets, while enhancing app performance and reliability.
• Driving Global Expansion & Stability – Delivered software to handle 30+ restaurant parameters, aligning digital and store calculations. Owned stakeholder communication, revamping 3rd-party order integration with our software, tax implementations digital order history unification, and built a processor for real-time kitchen order status tracking.
• Chosen for High-Impact Initiatives – Representing the ordering capability on a lead market adoption squad to accelerate software time-to-market & app launches in 4 major markets (in addition to the US) & ensure real-time production stability.

Software Engineer 1

Sept 12th 2022 - Sept 30th 2023
Chicago, Illinois

• Core Backend Engineer – Developed and maintained RESTful API software for digital order validation, totalization, and fulfillment in the McDonald’s app across global markets. Implemented backend fixes for 10+ promotions across multiple countries and added software implementation for 10+ offer types, optimizing for seamless upgrades.
• Enhancing Software Automation & Compliance – Built 20+ Postman collections for automated software verification, improved test coverage across 5+ services, adapted existing code to account for tax regulations in various global markets.

Software Engineer, Matician, Inc

Nov ‘21 - Sept ‘22
San Francisco Bay Area, California

• Working on computer vision & deep learning algorithms, as an integral member of the Perception Software Team.
• Designed, implemented a computer vision SLAM benchmarking pipeline, using data version control & visualization tools.
• Automated the calibration of robots, reducing the necessary human-involvement from >1.5 hours to 5 minutes per robot. Pipeline successfully used in > 100 calibrations to date. Tracked, analyzed mechanical causes behind calibration defects - helping mech. engineers design a superior crown.
• Worked on autonomous docking of robots; implemented algorithm able to estimate pose of the dock with < 4cm translational and negligible rotational error from within 25cm of the dock.
• Integrated stereo camera rectification tests w/ internal UI, allowing anyone to quickly (2-3 mins) test camera calibration.

Lead, Developer Student Club by Google Developers

Jan ‘19 - Jul ‘20
India

• Conducted over 7 workshops & hackathons; trained over 300 students on campus; increased student participation to 3-digit registrations.
• Invited (and sponsored) to the India DSC Summit by Google Developers at Goa, India

IIT Madras Research Park HTIC MedTech Incubator

May ’19 — July ’19
Chennai, India
Developed a prototype for predicting the presence/absence of chronic kidney disease in patients, using case based reasoning in artificial intelligence.

Leeds Beckett University

Feb ’18 – July ’18
Leeds, UK
Conducted research on ‘Software Engineering Approach to Software Bug Prediction Models Using Machine Learning as a Service’, resulting in a conference paper that was subsequently expanded into a book chapter, please see publications.

Seyyone Software Solutions Pvt. Ltd.

Nov ’17 – Jan ’18
Coimbatore, India
Involved in various data science and machine/deep learning activities. Built a retrieval based chatbot with neural networks.

Undergraduate Student Researcher

Sept ‘17 — Jul ‘20’
Smart Spaces Lab, Amrita School of Engineering
Worked on object detection & submitted my findings to the lab - ‘An Extensive Study and Comparison of the Various Approaches to Object Detection using Deep Learning’.