Built and scaled large-scale monitoring and analytics platforms supporting incident investigation and product health at scale, spanning interactive analytics UIs and distributed data aggregation pipelines for real-time and historical analysis.

Architected and delivered unified monitoring and reliability workflows from scratch using Hack, PHP, React, GraphQL, Thrift, Python and other services, enabling scalable oncall operations, reusable system components, and long-term platform extensibility across teams.

Designed and implemented agent-based investigation tooling using LLM-backed systems, focusing on robust orchestration, fallback handling, and evaluation workflows to improve analysis accuracy and operational efficiency in production environments.

• Enhanced security and user experience for Walmart Health Virtual Care platform by developing an advanced secure logout mechanism leveraging cookie analysis, dynamic user redirection, and integration with ID OL services, utilizing backend technologies.

• Improved system security and user privacy by establishing a robust mechanism for clearing authentication-related cookies using advanced cryptographic techniques and integrating with Redis and Elasticsearch.

• Streamlined user experience and maintained engagement by engineering a complex redirection system to guide users to appropriate URLs based on their account types after logout, ensuring seamless API transitions.

• Ensured real-time accuracy in user data handling by collaborating cross-functionally to transition from mock service to live ID OL service responses, leveraging SQL databases.

• Aligned project outcomes with organizational goals by working closely with cross-functional teams and stakeholders to refine and implement service features for Walmart Health platform, using React and JavaScript.

• Integrated the Consent Table into the Gen V1 ingestion pipeline using Informix triggers and stored procedures for real-time metadata synchronization. Optimized trigger mechanisms with SQL adjustments to support both batch and single packet processing, ensuring reliable data transfer for Consent Table entries.

• Developed validation logic and replay functionalities for Consent Table data packets, using Python to implement packet verification checks and SQL scripts to perform in-depth data validation. These enhancements enabled efficient handling of missed or corrupted packets, ensuring data integrity and regulatory compliance.

• Configured batch synchronization parameters to manage large datasets effectively, especially for RDM and drug tables. Utilized Python scripts to monitor and manage processing queues, balancing load distribution across Gen V1 processes to handle high-priority data efficiently.

• Revamped the monitoring alert system by rewriting Jenkins scripts in Python and integrating with Google Cloud Functions, leveraging Google Cloud Scheduler for efficient, automated monitoring and notification through email, Slack, and XMatters.

• Developing Dialog Connector simulator for the Walmart Contact Center AI Platform from scratch, crucial for IVR system testing, simulating real-world interactions and incorporating Text-to-Speech and Speech-to-Text functionalities.

• Played a key role in enhancing Walmart's CCAI platform, enabling integration with telecom providers like Avaya, InContact, Cisco, and focusing on AI and NLP-driven customer service improvements.

• Spearheaded HIPAA compliance efforts for major services such as Converse, Comex, and CCAI, replacing non-compliant elements, enforcing data access controls, and integrating audit logs with Splunk for enhanced data security.

• Developed a Kafka Connect Service (KaaS Sink Connector) for CCAI and Converse, crucial for managing and storing logs in Google BigQuery, significantly boosting data analysis and system monitoring.