Dec 2023 – Apr 2024 · 4 mos

• Designed and developed a real-time merchandising and monetization engine powering in-app ad placements for brands and vendors, built on Kotlin, Redis, Azure EventHub, and Cosmos DB. Designed a scalable, fault-tolerant backend supporting high-volume ad requests and ensuring consistent low-latency performance under load.
• Engineered a Redis-based ad tracking counter leveraging composite keys (buyer + ad-id + timestamp + time-unit) to precisely measure impression frequency and enforce ad-serving limits. This mechanism eliminated ad repetition, improved fairness in auction delivery, and enhanced real-time campaign targeting accuracy.
• Optimized ad-serving latency to under 80 ms (p99) by introducing async event pipelines via Kafka/EventHub, caching strategies, and Solr-based relevance search. The resulting system drove higher partner visibility, improved CTRs, and unlocked scalable, in-house monetization without relying on third-party ad networks.

Aug 2023 – Apr 2024 · 8 mos

• Designed and developed Quantity Purchase Scheme (QPS), a slab-based rewards platform assigning weekly and monthly purchase targets by order volume or value. Designed a rule-driven evaluation system where each order was asynchronously processed via message queues, validated against active targets, and marked achieved post-return window. Automated reward computation through background jobs that credited redeemable points to buyer wallets, improving engagement and repeat purchases.
• Implemented a facet-based coupon scheduler leveraging async indexing on category, SKU, and buyer attributes, enabling fast and targeted coupon evaluation. Achieved P99 latency under 100ms, enhancing responsiveness and coupon discovery for users.

Jan 2022 – Aug 2023 · 1 yr 7 mos

• Designed and developed a multi-tenant Coupon Orchestration Platform using Kotlin, Azure Cosmos DB, and Redis to serve personalized offers across Food, FMCG, Home&Kitchen, and Electronics categories. Improved search accuracy and scalability to ~2K RPS, while optimizing compute usage, reducing CPU requirements by 50% across multiple deployments.
• Built Prometheus and Grafana dashboards tracking coupon usage, redemption, and fill rates across segments, helping engineering and product teams monitor real-time effectiveness and optimize offer strategies.

May 2021 – Jan 2022 · 8 mos

• Enhanced existing promotions admin console, enabling granular CRUD operations across multiple levers such as Deal of the Day, Seller Promotions, and large-scale platform events like Mega Bharat Sale.
• Added comprehensive audit capabilities to the admin console, ensuring traceability, accountability, and compliance for all promotional and configuration changes.
• Developed backend capabilities for multi-slab discounts in food and FMCG categories, supporting buyer-level targeting and hierarchical catalog-based rules across verticals, listings, and sub-categories.

Aug 2020 – Aug 2020 · 0 mo

• Won the MIT COVID-19 Challenge (India Turning the Tide) out of 1500+ participants and 4000+ applicants worldwide.
• Worked on strengthening the coordination across the healthcare institutions (public and private) to build a robust ecosystem.
• I along with my team presented an idea to create an interface for connecting convalescent plasma donors with patients seeking for COVID-19 treatment.

May 2019 – Apr 2021 · 1 yr 11 mos · Bengaluru, Karnataka, India

• Delivered key modules like Direct Debit Mandate (EU), Fleet Maintenance, and Pool Syndication for a leasing SaaS product, leading to 20% faster onboarding for European clients.
• Enhanced core product based on complex client use cases; improved code reliability and reduced defects via rigorous test automation and debugging workflows.

Dec 2018 – May 2019 · 5 mos · Bengaluru, Karnataka, India

• Contributed to bug fixing, performance tuning, and feature enhancements in the existing product based on client feedback and change requests, improving system stability and user experience

Jul 2018 – Sep 2018 · 2 mos · Bengaluru Area, India

• Worked on Deep Learning and DevOps initiatives focused on delivering Al-driven solutions for client products.
• Developed a Face Recognition prototype using state-of-the-art deep learning architectures such as ResNet, MTCNN, YOLO, OpenFace, and DLib, ensuring high accuracy across varied datasets and lighting conditions.
• Integrated the face recognition capability as a REST API into the client's existing product, enabling seamless deployment and scalability within their production environment.
• Gained hands-on experience in model training, inference optimization, and API deployment pipelines, bridging the gap between research and real-world application

Mar 2018 – Mar 2018 · 0 mo

• Won national level Hiring Hackathon organized by Odessa
• Developed a small-scale Vehicle Leasing application on Android. I was among the four developers in my team at the hackathon. Won the job offer from Odessa for the profile of Software Developer and work on LeaseWave.
• LeaseWave is an equipment finance software system that provides lease and loan management for the entire lifecycle of the contract and the entire lifecycle of the asset.

Dec 2016 – Jan 2017 · 1 mo · Patna Area, India

• Analyzed and documented the existing automation processes to identify bottlenecks and improvement opportunities within operational workflows.
• Proposed and implemented process enhancements aimed at increasing productivity, reducing manual effort, and improving overall efficiency.
• Worked as part of a third-party company supporting Hindustan Unilever Limited, contributing to automation and productivity improvement initiatives aligned with business objectives.

Oct 2016 – Dec 2018 · 2 yrs 2 mos · Chennai Area, India