Toyanath Pandey

• Developed backend systems and data processing pipelines for GLUH research project. • Implemented data ETL pipelines and stream processing systems for research-oriented data analysis. • Designed scalable architecture utilizing cloud-native technologies (Docker, Kubernetes) for research platform deployment. • Developed REST APIs and microservices for integration with graph learning frameworks and machine learning pipelines.

• Designed and developed REST APIs to improve software integration and backend functionality. • Implemented new features for a Diagnostic Trouble Code (DTC) interpreter to streamline log management and code interpretation. • Collaborated on the development of an automotive video device using Raspberry Pi. • Used Splunk for debugging, log analysis, and feature development. • Automated build and deployment processes using Jenkins.

• Developed Python-based tools to enhance internal software functionality. • Built integrations using the JIRA REST API to automate ticket creation and cloning. • Designed a user-friendly interface for in-house APIs. • Contributed to backend automation for log processing and diagnostics.

• Developed GUI-based applications using Python, C++, and Qt. • Applied agile development methodologies for timely delivery of high-quality software. • Implemented CI/CD automation and performed testing and debugging. • Collaborated with cross-functional teams to improve software quality.

• Performed penetration testing for web and mobile applications following OWASP guidelines. • Conducted log analysis using ELK stack to monitor security incidents and system performance. • Configured firewalls, VPNs, proxies, and network security policies. • Performed risk assessments and recommended mitigation strategies.