• Orchestrated migration of 45+ policies for a level-0 service via AI-assisted workflows (Cursor/OpenSpec), automating task breakdown, PR generation, attestation, and shadow-mode validation ensuring signed transaction integrity and consistency

• Engineered an AI-driven incident response agent integrated with Slack alerts and DynamoDB to automate root-cause analysis and downstream service orchestration, reducing Mean Time to Resolution (MTTR) by 45% for critical transactions

• Optimized system performance via a DynamoDB caching layer (GSIs) and Golang gRPC endpoints, slashing data retrieval latency from 250ms to sub-150ms and streamlining CI/CD with automated E2E testing

• Restructured end-to-end code flow for ingesting and processing legal entity metadata via Kafka, improving data reliability by 30% and reducing processing latency by 25%

• Implemented amount-based rate limiting across 90%+ of entity transactions, reducing transaction exposure risk by 35%

• Spearheaded a tier-based layered parsing and validation security system, eliminating a core single-point-of-failure and mitigating more than $1B in transaction-manipulation risk

• Pioneered a unified observability layer for 10+ risk heuristics, cutting metric duplication by 40% and enabling real-time, asset-level high-risk monitoring via Datadog dashboards

• Engineered critical security controls, including an instant-response kill switch and adaptive policy enforcement system, reducing fraudulent transaction exposure by 40% and improving real-time detection and response times by 60%

• Designed a config-driven anomaly framework with automated E2E testing, slashing policy update latency to sub-100ms

• Architected high-availability Java/Spring Boot RESTful APIs to support 10K+ daily requests, enhancing backend reliability and cross-platform integration for third-party partners

• Accelerated product delivery by building React.js UIs and automating Jenkins CI/CD pipelines for frequent deployments

• Scaled cloud infrastructure via AWS Lambda and DynamoDB, achieving a 25% reduction in system downtime

• Fine-tuned MongoDB and MySQL schemas to ensure data integrity for 500K+ daily high-volume transactions

• Standardized code quality through JUnit/Mockito testing, raising coverage and streamlining the peer-review process

• Streamlined high-throughput Salesforce ETL pipelines, ensuring real-time ingestion of 100K+ daily records

Built React.js, Redux, jQuery, and Tailwind CSS components using Figma designs, and developed Grafana dashboards

• Developed and maintained Go RESTful APIs for real-time data handling, leveraging GraphQL for data querying and storage

• Maximized Databricks pipeline efficiency by 33%, improving data quality, and system reliability

• Delivered AngularJS, Spring Boot, Java, and Kotlin components across 3 panels: customer, administrator, and supervisor

• Integrated Apache Solr search, Jenkins CI/CD, and OAuth authentication to optimize query performance and security

• Automated UI and API tests using JUnit, Mockito, Gherkin, and Selenium, improving coverage and reliability

• Participated in Scrum and containerized applications using Docker and Kubernetes, improving deployment efficiency

• Constructed PySpark and Informatica ETL pipelines to process high-stakes loan-risk assessments for 7.5M customers, ensuring strict regulatory compliance and accuracy through rigorous data validation and JIRA-tracked sprint cycles

• Fortified pipeline monitoring using Splunk and Bash scripting to oversee 100+ daily jobs in Linux/UNIX environments, achieving 99.9% reliability and drastically reducing manual intervention for critical data ingestion

• Provisioned AWS infrastructure and automated Airflow workflows, optimizing S3 and Athena pipelines for massive dataset

• Upskilled 4 colleagues on AWS and Airflow, improving team engineering productivity by 30%