Tamil Selvan

Staff-level backend engineer with 9 years of experience architecting cloud-native distributed systems, CI/CD automation platforms, and scalable REST APIs using Python (FastAPI, Flask). At Zoho, reduced deployment time by 30% and improved reliability by 35% by transforming monolithic systems into Docker-based microservices. Experienced in integrating AI-powered deployment intelligence using LangChain and LLMs, applying structured log analysis, contextual prompt design, and data-driven CI/CD optimization.

Provides architectural direction and mentors engineers across backend engineering and automation systems.

Member Technical Staff at Zoho Corporation (2017-03 – Present)

• Led the architecture and implementation of CI/CD automation systems, achieving a 30% reduction in deployment time and enhancing operational efficiency.
• Developed and deployed scalable microservices for build and mobile app deployment, ensuring reliability and scalability in production environments.
• Transformed monolithic automation systems into Docker-based microservices, improving system reliability by 35% and streamlining workflows.
• Engineered RESTful APIs using FastAPI and Flask to support deployment automation frameworks, enabling seamless integration across systems.
• Integrated Google and Apple APIs to automate mobile application publishing workflows, reducing manual intervention and increasing efficiency.
• Optimized build artifact reuse across data centers, significantly reducing manual operational efforts and improving resource utilization.
• Automated on-premise product publishing to AWS, contributing to a 25% increase in revenue growth through enhanced deployment capabilities.
• Utilized Databricks to enhance data processing workflows, enabling efficient handling of large-scale data and improving system performance.
• Generated actionable build analytics and deployment reports using structured data analysis with Pandas and NumPy to improve engineering decision-making.
• Developed GenAI-based deployment intelligence solutions using LangChain, implementing prompt templates, chains, and agents to analyze CI/CD logs and generate structured JSON insights.
• Built a Flask-based AI web application to expose LLM-powered deployment diagnostics and integrate intelligent debugging support into internal automation tools.
• Applied model evaluation strategies to compare LLM performance and select optimal models for reliability and deployment use cases.
• Explored AI-driven automation enhancements using machine learning and generative AI workflows to improve deployment intelligence.
• Mentored junior engineers and conducted comprehensive code reviews, fostering technical growth and enhancing team productivity.

Master of Computer Applications – Loyala Institute of Technology (2011)

Bachelor of Science in Chemistry – Kandasamy Kander's Arts & Science College (2008-06)

HSC – Kandasamy Kander's Hr. Sec. School (2005-06)

SSLC – Kandasamy Kander's Hr. Sec. School (2003-06)