• Owned multiple end-to-end Python microservices and APIs, conducted low-level design reviews and delivered across both microservice and monolithic architectures.

• Led large-scale optimization of FCO’s Python microservices (ArangoDB, Kafka, Kubernetes), resolving bottlenecks to increase system scalability from 5K to 50K+ telemetry endpoints and cut infrastructure costs through efficient resource utilization.

• Drove production hardening through observability (Prometheus metrics, health probes, alerting), dedicated debug interfaces, and proactive monitoring—reducing customer-found defects.

• Prototyped AI-driven self-healing agents, demonstrating potential for autonomous monitoring and cost reduction.

• Designed and implemented a relay agent on embedded systems to relay telemetry between devices and the cloud and dispatch the results back to the edge device.

• Increased system load capacity 10× by identifying scale bottlenecks and delivering the first scalable iteration of the core agent. Increase system scalability from 2K to 20K+ telemetry endpoints.

• Designed and implemented a production-facing debugging aggregation API for a distributed microservices platform, enabling developers to retrieve comprehensive diagnostic data through a single REST endpoint.

• Developed orchestration logic in Python to automate production diagnostics, reducing manual debugging effort and accelerating incident resolution.

• Deployed and maintained containerized services using Docker and Kubernetes, contributing feature enhancements to improve service modularity and reliability.

Graduate Teaching Assistant (Course Producer) for CSCI 102 - Fundamentals of Computation

• Owned the design and implementation of automated testing infrastructure for a 7-service Python microservices platform, introducing CI-integrated validation where none previously existed.

• Built containerized test pipelines using Docker, Kubernetes, Jenkins, and Git, enabling consistent local and production test execution and improving deployment reliability.

• Developed comprehensive unit test suites with coverage reporting, enabling automated regression detection and reducing production defects.

• Responsible for managing Machine Learning POC’s for clients including sales prediction, medical diagnosis etc.

• Designed and built a model on Diabetic Retinopathy with 86% accuracy.

• Created custom Convolutional Neural Networks and used transfer learning from prominent models.