Oct 2021 – Aug 2022 · 10 mos

• Part of Amazon Advertising business, I manage multiple cross functional software teams which are responsible for advertising billing, budgeting and campaign management. Responsibilities include technical strategy, goal planning, tech design and development, project and stakeholder management.

Dec 2017 – Sep 2021 · 3 yrs 9 mos

Apr 2017 – Nov 2017 · 7 mos

• Led the mixed team of 10 SDEs ( software and embedded engineers) across geographies to design and deliver a IoT based product to improve production efficiency in Amazon warehouses. The product help realize a cost savings of $19m/yr across WW delivery network.

Apr 2014 – Mar 2017 · 2 yrs 11 mos

• Designed and Developed the next generation WebStack framework 'SWIPE' empowering the on boarding experience for Sellers @ Amazon. The framework is build on the premise on configurability, reusability and simplicity for the users, It abstracts the web architecture complexity from adaptors and
• allows the reusability of components. Apart from SWIPE,also designed and developed multiple distributed and scalable software/services

Apr 2012 – Mar 2014 · 1 yr 11 mos · Bangalore

• Working in the Domain of Online Marketing which is mainly responsible for generating Traffic for product website through rigorous Online Marketing Campaigns. Building the tool for push marketing and managing campaign across various channels like Email, SMS, push notifications etc.
• Team : Online Marketing
• Responsibility & Role : Traffic generation through Email Marketing, Designing User-targeted
• Campaign through Machine Learning,
• Challenges : throughput, Audience Coverage, Audience Targeting, Recommendation Generation.
• Technologies : Java, MySQL , Hbase, Scala, Tomcat

Jul 2011 – Mar 2012 · 8 mos · Bengaluru Area, India

• Worked as API Developer for Yahoo!'s Rightmedia Exchange, (Non-Guaranteed Digitial Display Ad Exchange).

May 2009 – Jul 2009 · 2 mos · Gurgaon, India

• Automated the Classification and Validation for Network Anomalies like Port Scan, Network Scan, Denial of
• Service Attack, etc. using the Network flow Information by building a network Anomaly classifier capturing their characteristics and features, in less than 2 months

May 2008 – Jul 2008 · 2 mos · Paris, France

• Ported OpenCV operators to GpuCV which took the advantage of the high level of parallelism and computing power of graphics processing units (GPUs) to speed up the performance also, used Nvidia Cuda Kernels, to speed up image processing for operations like Object detection and Fourier transform