San Francisco Bay Area
Visionary Agentic AI, ML, and engineering leader for 25+ years defining and executing enterprise Data and AI strategy, building scalable platforms, and leading global teams across regulated, B2B, and B2C industries at Google, Ancestry, Aisera, and Automation Anywhere. PhD in Computer Science and MBA degrees, CFA Charterholder bridging deep technical expertise with investment acumen and business strategy. Architect and scale agentic AI platforms and production ML systems — orchestration, retrieval, memory, guardrails, multi-agent systems, and edge deployment — delivering end-to-end from ideation through production optimization. Lead LLM integration, RAG retrieval with graph-based reasoning and long-context scaffolding, prompt and context engineering workflows, and rigorous benchmarking of AI reasoning, latency, and agent performance. Define and enforce MLOps standards for production lifecycle, monitoring, and scalability across cloud and hybrid environments. Built and scaled multidisciplinary AI, data science, and analytics organizations from the ground up. Establish AI Centers of Excellence with governance, standards, and cross-functional alignment. Lead sprint planning, backlog refinement, and release cycles. Drive enterprise-wide AI adoption through enablement, change management, upskilling, and HR partnership. Lead enterprise data modernization, data governance, and infrastructure strategy — ensuring data quality, metadata standards, privacy, and security. Design AI-enabled automated workflows across enterprise systems. Build revenue and channel performance forecasting using advanced statistical and ML methods. Define and standardize LTV measurement, retention drivers, and data-driven planning for budget allocation and growth. Drive presales, advisory, and client engagement to sell and deliver AI solutions. Validate product-market fit across key user groups. Manage AI vendor and partner ecosystems, budgets, and operational delivery. Translate commercial requirements into engineering programs with milestone-based execution. Represent the AI vision at client, academic, industry, and partner forums. Partner with executives and boards to align AI roadmaps with corporate objectives, translate data into actionable business value, and drive measurable ROI. Establish responsible AI governance across risk, compliance, ethics, HIPAA/PHI, and transparency. Co-Founder and Co-Chair of a well-known AI Leaders' Club, active investor, board advisor, and holder of multiple patents and peer-reviewed publications.
• Executive owner of enterprise AI strategy, multi-year roadmap, and agentic architecture for AI-powered automation serving 37% of Fortune 500 customers • Build, lead, and mentor AI scientist and engineering teams through hiring, standards, culture, enablement, and workforce development • Established responsible AI governance frameworks, policies, and controls across risk, compliance, ethics, and transparency • Led evaluation, selection, and productionization of LLM applications with RAG, prompt engineering, and evaluation frameworks • Designed and deployed AI-enabled automated workflows across enterprise systems to improve efficiency and decision-making • Defined and enforced MLOps standards and best practices for production model lifecycle, monitoring, and scalability • Developed benchmarking methods to assess AI reasoning, performance, interpretability, latency, and agent orchestration • Partnered with product, engineering, and business leaders to embed AI capabilities into core platforms and customer workflows • Identified AI-driven market trends and growth opportunities to differentiate offerings and strengthen competitive positioning
Strategic AI and Software Development guidance for building products used by global defense and dual use markets
● Lead the development and deployment (60+ customers, most are Fortune 500) of a multi-agentic, self-adapting AI enterprise platform designed to redefine how enterprises automate, learn, and adapt across business functions ● Designed and built several new core subsystems in the Aisera's AI platform ● Managed international (US/Europe/India) team of high performing ML engineers and AI scientists ● Lead x-functional team saving about 10% of all AI expenses. ● Built Agentic Conversational Intelligence, Self-Learning Agentic Planning and Orchestration, Intelligent Routing for LLM
I established and led a diverse, distributed world-class team of Data Science and Machine Learning engineers across multiple global offices. - Own and define the long-term AI and data science vision, strategy and roadmap. Provided strategic leadership in advanced analytics, AI, and ML platform engineering - Developed and implemented product vision, cross-functional collaboration across all functions including Product, Growth, Design, Platform, GTM and Support to manage success of cross-functional relationships and initiatives, and fostering a culture of trust, ownership, accountability, innovation, and continuous improvement. - I spearheaded major initiatives, managed large-scale data resource projects to ensure the successful delivery of scalable, reliable, and high-performance software solutions - Designed and implemented clear and repeatable engineering processes, balancing high quality, time to market, and costs
Led the advancement of major initiatives, focusing on science, technology, and business metrics, and oversaw the development, deployment, and testing of ML platform. Successfully built and managed a distributed team of engineers and scientists, prioritizing high-performance solutions tailored to customer needs.
Instructor/Lecturer Computer Science Department (Quantum Computing - ML and Security applications)