• Built production multi-agent system using LangGraph with Vertex AI (Claude and Gemini APIs) to automate scraper remediation - reduced manual fix time from full days to 10-20 minutes with human oversight, achieving 60% autonomous success rate. Implemented PII safety protocols, Datadog tracing, and observability for production LLM integration

• Remediate web scraping errors for financial institution connections maintaining reliable data aggregation across thousands of institutions and millions of member accounts

• Enhanced issue visibility and automation by building intelligent Jira system for lifecycle management - automates issue creation/closure/linking/ranking based on thresholds, Slack alerting, and deployment integration to prioritize remediation work

• Architect event-driven backend systems on GCP handling thousands of daily message queues via Pub/Sub, Cloud Scheduler, and asynchronous processing patterns using TypeScript/Node.js services

• Configure and manage production Kubernetes infrastructure using KCC, IAM, KMS encryption, External Secrets, service accounts, and secure inter-service communication

• Lead Frontend Engineer on a AI/ML project that processed data using various ML and AI services within an event-driven environment creating several successful transactions for the vendor.

• Architect for frontend React components and features throughout the application achieving demands for multiple clients in separate environments.

• Deployed to self managed Kubernetes and AWS environments, updating configuration templates in terraform, while also solving possible deployment hurdles.

• Design and construction of the entire Frontend UI using React with an overall aesthetic style, and user-centric interface transforming complex data into frontend displays combined with functional architecture from development to production level.

• Create UI prototypes for stakeholders to approve and migrated into code by creating reusable React UX components and maintaining all state logic to display data.

• Integrated cloud native services on AWS including S3, SNS, SQS, EB, and cloud agnostic services using RabbitMQ, and Minio in Kubernetes to the frontend via server-side configurations to achieve all necessary frontend functionalities.

• Consolidated data upload components including multipart uploads on the frontend central to processing large datasets for ML data to be displayed within the application.

• Implementation of any 3rd party APIs required for task completion including Open Ai GPT-3 models API for automation.

• Developed a brand new optimized design of main features on front end components including integrating text editing, and video editing tools to get ready for site launch.

• Optimizing components for responsive performance on desktop and tablet browsers.

• Maintaining and building reusable components for future use while creating proper type safe using mainly React Node and Typescript.

• Translating architectural design into efficient readable and reusable code using standard coding conventions.

• Maintained site functionality with team updating pull requests and grooming program daily.

• Tasked with developing an automated scraper tool for extraction of data.

• Created functional data retrieval with Node.js React, JavaScript using a Headless Browser via Puppeteer for web automation.

• Produced UXUI designs using React to production while working with the QA testing to improve program performance features.

• Created a website for companies using React, Node, TypeScript and various CSS Libraries.

• Designed and deployed responsive and lightweight applications for clients meeting all deadlines throughout.

• Continuously assessed the clients needs and themes to create a fast and responsive sleek design that represents the brand and commercial value.

• Consistently kept speed optimization and performance features high while maintaining all fundamental features.