• Built and improved feature-store and model-serving infrastructure for Snap's ML platform, supporting user, document, and ads feature systems across both batch and online processing at 2B-scale data volume and trillion-scale daily feature events.

• Developed CI/CD automation, feature access pipelines, and orchestration for ML model-serving workflows, accelerating deployment time-to-production by 2× and strengthening production reliability and real-time feature availability.

• Strengthened observability and incident recoverability for ML workflows operating at billion-scale prediction traffic, enabling more consistent feature production in large-scale recommendation systems.

AI-Ready Data Infrastructure & Real-Time Streaming Platform

• Architected Amazon's ASIN data platform from batch ETL to real-time Kinesis-based streaming, reducing duplicate events by ~300× and delivering ~16× faster processing across ~10M ASINs.

• Cut archival lag from 12+ hours to near real time via deduplicated record emission.

• Integrated Bedrock and SageMaker, building real-time Parquet datasets and low-latency feature-serving layers — achieving 2.5× faster data-serving and 3× inference throughput at scale.

• Built an LLM-powered feedback pipeline extracting sentiment and shopper intent signals, driving 15% lift in customer satisfaction scores.

Agentic Workflow Orchestration Platform

• Designed and built a unified orchestration platform for Buy for Me, raising observability from ~25% to >95% and enabling full journey traceability.

• Reduced manual interventions by 4×, cut incident resolution by 6×, and lowered operational cost by ~$200K/year via workflow standardization and automated remediation.

• Enforced idempotent, deterministic execution reducing defects by 60% and cutting onboarding time by 10× (~2 weeks → ~1 day) across 5+ teams.

• Built platform primitives for human-in-the-loop and agentic automation, enabling AI-native workflows on Buy for Me.

Distributed Checkout & Payments Platform — Shop with Points

• Owned end-to-end architecture and launch of Shop with Points for Buy with Prime, spanning payments, refunds, loyalty integration, and merchant systems for ~1M merchants.

• Standardized 5 checkout APIs and redesigned payment domain models with idempotent refund flows, driving ~9,000 incremental orders/week and ~$500K–800K/year in rewards redemption.

• Designed fault-tolerant transaction pipelines ensuring zero-loss payment processing and seamless failover — cutting incident response time by 30%.

• Built and shipped backend API features for Unibit API, a Java-based financial data platform serving standardized market data to 1,000+ paid enterprise customers including Accenture and Salesforce.

• Developed and enhanced backend APIs for the Data Terminal, a financial dataset platform built for analytics and commercial decision-making.

• Improved data reliability, API performance, and usability across both platforms through iterative backend development and cross-functional collaboration with product and engineering teams.