- Designed and developed APIs using FastAPI and MongoDB, creating dynamic endpoints that improved data handling, retrieval, and application responsiveness.- Deployed microservices on Kubernetes using Helm charts, ensuring seamless scaling, faster deployments, and efficient resource management.- Implemented a comprehensive observability stack by integrating Grafana, Prometheus, Loki, and Tempo with OpenTelemetry. This enabled detailed monitoring, logging, and distributed tracing across both gRPC and HTTP interactions, improving system reliability and providing deeper insights into performance and bottlenecks.- Integrated deep learning algorithms, including Geometric Match and Superglue, for cloud-based inference with Hugging Face models. This streamlined the automation workflow, improved the speed and accuracy of visual recognition and enhanced the efficiency of various tasks.

- Developed Python-based APIs using FastAPI. Used MongoDB for storing Data.- Implemented advanced MongoDB queries, including aggregation pipelines, to efficiently process and analyze data.- Applied Pydantic for input validation, ensuring that all incoming data met specified criteria before processing. This approach maintained data integrity and improved error handling.