• Worked on AI-powered eCommerce optimization and fraud detection, integrating BigCommerce’s platform with generative AI and ML pipelines to analyze customer behavior, detect fraudulent transactions, and deliver real-time product recommendations and risk scoring, collaborating with product, data science, and engineering teams.

• Built scalable backend microservices in Python using FastAPI, SQLAlchemy, and PostgreSQL, implementing asynchronous task queues with Celery and Redis caching, and designing RESTful APIs for order management, fraud detection, and recommendation systems, improving API response time and throughput by 40%.

• Developed dynamic merchant dashboards using React, React Query, Redux Toolkit, and Chart.js, enabling real-time sales analytics, customer insights, and AI-driven recommendations via WebSocket integration, reducing reporting time by 35% and improving decision-making.

• Implemented secure authentication and authorization using OAuth2 and JWT, integrated SSO via AWS Cognito, and enforced role-based access control (RBAC) for merchants and admins, ensuring compliance with data security standards and improving platform security posture.

• Built and maintained CI/CD pipelines using GitHub Actions and AWS CodePipeline, automating testing (unit, integration, and E2E), enforcing code quality with SonarQube, and improving deployment reliability across microservices and frontend applications.

• Containerized applications using Docker and deployed on Amazon EKS with Helm charts, integrated Kafka for event-driven order and inventory processing, and implemented monitoring using Prometheus and Grafana, ensuring high availability and scalability of the platform.

• Developed a cloud-based Industrial IoT (IIoT) and Smart Manufacturing platform, collaborating with product managers, QA teams, and DevOps engineers in Agile sprints, improving sprint efficiency by 25% while ensuring scalable, secure, and high-performing enterprise-grade architecture.

• Built highly responsive frontend modules using Angular, leveraging NgRx for state management, RxJS for reactive programming, and lazy loading techniques, improving application performance by 35% while developing reusable, maintainable components for large-scale industrial applications.

• Implemented centralized state management using NgRx Store, Effects, and Selectors, enabling predictable state transitions, efficient data flow, and simplified debugging, effectively handling complex workflows in connected manufacturing modules.

• Designed and optimized PostgreSQL databases deployed on Azure cloud infrastructure, implementing indexing, partitioning, and caching strategies to reduce query latency by 45%, while ensuring high availability, fault tolerance, and consistency for large-scale industrial telemetry and analytics systems.

• Developed backend microservices using Python and FastAPI, building scalable RESTful APIs and asynchronous services, improving system throughput by 40% and reducing API response times by 35% through modular microservices-based architecture for IoT device management and analytics.

• Implemented secure authentication and authorization mechanisms including JWT, RBAC, encryption protocols, and input validation, ensuring compliance with OWASP and industrial security standards, reducing critical vulnerabilities by 50% and safeguarding sensitive enterprise and operational data.

• Developed comprehensive unit and integration tests using pytest and Jest, achieving 92% test coverage, reducing production defects by 28%, and improving code quality through automated testing, continuous integration pipelines, and proactive defect detection practices.