Anil Thomas

I'm an Enterprise and Security Architect with over 22 years of experience designing and securing complex, large-scale enterprise systems. I've spent my career focusing on building resilient, scalable, and compliant digital infrastructures that protect against evolving threats and support business growth. I'm now pivoting to the fascinating world of Agentic AI and Machine Learning. I'm actively applying my deep-seated knowledge of governance, security, and system design to the unique challenges of building and deploying autonomous AI agents. I believe the principles of zero trust, data lineage, and privacy by design are not just relevant but critical to ensuring the responsible and secure development of AI. My current interests and projects on Hugging Face include: Secure MLOps (Machine Learning Operations): Exploring how to apply DevSecOps principles to the entire AI lifecycle—from data ingestion and model training to deployment and monitoring—to prevent data poisoning, model tampering, and other AI-specific vulnerabilities. AI Agent Security: Investigating the security of multi-agent systems, focusing on how to secure tool orchestration, manage inter-agent communication, and implement robust access controls for AI agents. Agentic AI for Cybersecurity: Developing proof-of-concept models and agents that leverage my background to enhance threat detection, automate incident response, and perform proactive threat hunting. This platform is a key part of my journey. I'm excited to collaborate with the community on open-source projects, contribute to datasets, and share my unique perspective on building the next generation of secure, agentic systems. Feel free to connect with me to discuss AI security, enterprise architecture, or potential collaborations.