As Principal AI Engineer, led the design and deployment of agentic AI and enterprise GenAI capabilities within SAP BTP for financial analytics transformation. Architected and implemented the PaPM Joule AI Chatbot, integrating LLM-based orchestration with FastAPI microservices to enhance data-driven decision-making for enterprise finance users. Key contributions include: Architected multi-agent systems using GPT-4o, Claude, and Gemini for SAP AI Core, enabling intelligent data retrieval, PII-safe automation, and human-in-the-loop governance. Built Enterprise Search with HANA MCP Server for fine-grained data governance and contextual analytics across business entities. Optimized GenAI backend performance — achieving 95% faster processing and 60× query acceleration through Redis caching, SQL Agents, and FastAPI tuning. Partnered with product leadership and executives to shape the AI roadmap and business transformation strategy, aligning customer feedback with innovation priorities. Conducted internal GenAI capability uplift programs, mentoring engineers in LangChain, CrewAI, and LangGraph for scalable, compliant enterprise AI adoption. This role bridges AI innovation, enterprise architecture, and business transformation, demonstrating measurable impact in system intelligence, compliance, and operational efficiency.

Led enterprise-scale Generative AI and platform modernization initiatives across GE Healthcare’s imaging and diagnostic systems, combining AI innovation with mission-critical software engineering. Architected and deployed the internal GenAI Platform enabling secure, compliant LLM usage across global teams while maintaining healthcare IP integrity. Key contributions include: Built agentic LLM systems (CODE GPT, MICT GPT, Service GPT) to automate code discovery, service troubleshooting, and documentation search — improving developer productivity by over 40%. Designed and implemented RAG pipelines with LlamaIndex and Qdrant, introducing measurable GenAI evaluation via RAGAS metrics. Developed the Intelligent Service Platform with autonomous AI agents for predictive issue resolution — reducing service incidents by 80% and earning US Patent 7011605-US-1. Drove CT workflow modernization, migrating legacy monoliths to microservices with Spring Boot, enhancing scalability and compliance across imaging systems. Collaborated cross-functionally with product, security, and regulatory teams to ensure AI readiness, data governance, and model observability in healthcare environments. This role demonstrates expertise in agentic AI system design, AI-driven automation, and digital transformation across a regulated enterprise ecosystem.

Engineered high-performance storage management systems and automation tools that accelerated enterprise infrastructure delivery and operational efficiency across EMC product lines. Designed and delivered Solutions Enabler APIs for EMC storage arrays, reducing deployment time by 90% and improving interoperability across enterprise systems. Key contributions include: Developed performance monitoring and automation frameworks, improving system efficiency by 30% and reducing manual intervention through predictive analytics. Automated build and deployment pipelines using PHP and Perl, achieving 60% faster release cycles and early-stage DevOps enablement. Collaborated with global teams on API architecture, scalability optimization, and distributed system reliability, setting the foundation for data-driven, modular platform engineering. Mentored junior developers and drove engineering best practices that improved API quality and maintainability across releases. This role established a strong foundation in systems engineering, automation, and performance optimization, which later evolved into designing AI-driven and agentic enterprise systems in subsequent roles.