New York, New York, United States
I advise enterprises, investors, and operating leadership on AI governance in environments where regulation, compliance, and operational complexity intersect. The focus is on applied AI and agents: how models are evaluated, constrained, and embedded into real workflows without breaking risk, control, or regulatory expectations. This work draws on decades of building, scaling, and exiting global businesses across marketplaces, Amazon-led commerce, financial services exposure, and cross-border operations spanning China, Europe, and the United States. Having operated under inventory risk, tariff regimes, AML/KYC controls, data limitations, and regulatory friction, I bring a systems-level view of where AI safely creates durable advantage — and where it introduces new, unacceptable failure modes. In parallel, I work with a confidential frontier AI research lab as an independent consultant on model evaluation and reinforcement learning from human feedback (RLHF). The emphasis is on training and governing advanced models: defining qualitative criteria, scoring complex multi-response outputs, and aligning model behavior with the standards that regulators, boards, and institutional clients actually expect. Advisory work concentrates on: • AI governance, compliance infrastructure, and human-in-the-loop control systems • Model evaluation, RLHF signal design, and workflow-level guardrails • Marketplace and platform strategy under regulatory and policy pressure • Cross-border scale, trade structure, and risk exposure decisions • Second-opinion counsel on high-consequence strategic choices at board and owner level Engagements are limited and advisory in nature, suited to situations where judgment, regulatory awareness, and global operating experience matter more than execution capacity.
Model Evaluation & RLHF: Contribute to reinforcement learning from human feedback (RLHF) programs for a frontier AI research lab, evaluating how advanced models reason, handle edge cases, and behave in quasi-regulated, high-stakes workflows. Apply decades of global business judgment to distinguish model outputs that are technically correct from those that are strategically sound, institutionally credible, and operationally deployable. Governance-Driven Criteria Design: Translate regulatory, compliance, and institutional expectations into concrete evaluation criteria and scoring rubrics that shape how models are trained, tuned, and deployed. Draw on direct experience with AML/KYC frameworks, cross-border trade compliance, and platform governance to stress-test model outputs against real-world regulatory scenarios. Risk, Escalation & Guardrails: Assess model outputs for risk signals, failure modes, and escalation points; help design patterns where humans, policies, and orchestration layers constrain and supervise autonomous model behavior in enterprise and regulated contexts. Documentation & Auditability: Support the creation of evaluation records, rationales, and taxonomies that make model behavior more explainable, auditable, and defensible to regulators, clients, boards, and internal governance bodies. AI Surveys & Expert Consulting: Deliver structured AI expertise through expert network platforms, providing survey responses, qualitative research interviews, and consulting sessions on AI adoption, model governance, marketplace strategy, and enterprise operating models for institutional clients and research organizations. Throughput at Quality: Maintain high-volume, high-velocity qualitative assessments while preserving consistency, signal quality, and auditability, feeding structured feedback to model and product teams at frontier research pace.
Provide board-level advisory support on applied AI, enterprise operating models, and cross-border scale, including second-opinion counsel on high-consequence strategic decisions, leadership judgment, and organizational trust at the board and owner level.
Retained by institutional investors, hedge funds, investment management firms, professional services firms, technology companies, and ad-tech platforms through GLG, AlphaSights, Guidepoint, Third Bridge, Office Hours, Coleman Research, and Mercor to deliver expert advisory, qualitative research interviews, and structured surveys across high-value consulting domains. AI & LLM Expert Consulting: Recurring expert on LLM stack evaluation, foundation model selection, LLM API integration, AI coding tools, Enterprise AI applications, Consumer AI tools, Voice AI, Integrated AI assistants, AI data security, and AI adoption trends. Clients include enterprise technology firms, investment analysts, and research organizations benchmarking frontier AI products. Amazon & Marketplace Strategy: Channel checks on Amazon retail and advertising, marketplace seller economics, multichannel solutions, seller returns, capital financing on online marketplaces, CPG growth via Amazon Business, Shopify system integration, and competitive landscape analysis including Temu and Shein strategic positioning for investment research. Digital Advertising & Ad-Tech: Expert on digital ad spend across SMB and enterprise segments, AI-driven advertising automation, programmatic media planning, creator marketplace ad campaigns, conversational AI advertising, GenAI in advertising, ad monetization and attribution platforms, and retail-media advertising. Cross-Border & Trade: Advise on out-of-country fulfillment, tariff exposure, trade policy risk, brand accelerator operations in US and China, and cross-border marketplace scale decisions. Litigation & Compliance Consulting: Retained as expert witness candidate for retail apparel distribution and eCommerce litigation by business advisory firms working with leading law firms.
Serve as a member of the executive leadership team responsible for corporate strategy, market expansion, and long-term growth initiatives at NextReg. Provide strategic oversight across business development, market positioning, AI adoption, and commercial execution within financial services and technology sectors. Leverage extensive executive leadership and entrepreneurial experience to identify emerging market opportunities, evaluate strategic partnerships, support enterprise sales initiatives, and advise on business scaling strategies. Collaborate with leadership across product, technology, and commercial functions to align innovation with client needs and evolving industry trends. Advise executive leadership and stakeholders on developments in artificial intelligence, fintech, enterprise software, competitive dynamics, and broader financial markets to support informed strategic decision-making. Contribute to investor discussions, corporate development initiatives, and the execution of NextReg's long-term vision. Focus Areas: Corporate and growth strategy AI and emerging technology trends Enterprise market development Strategic partnerships and business development Go-to-market strategy and market positioning Financial services and fintech innovation Startup scaling and executive leadership Investor and stakeholder engagement This role brings a combination of executive leadership, founder experience, strategic planning expertise, and deep understanding of technology and financial market trends to support NextReg's continued growth and innovation.
Built and scaled a cross-border commerce platform from inception into one of Europe’s largest multi-brand Amazon private-label operators, active across the United States and multiple European markets. Over a 15-year period, designed and led end-to-end operating systems spanning product development, manufacturing, logistics, inventory, marketplace growth, and international expansion. Established China-based manufacturing operations and European fulfillment infrastructure, managing sustained growth across regulatory shifts, supply-chain volatility, and multiple market cycles. This work was executed largely before the availability of modern AI tooling, requiring first-principles thinking in data, process design, incentives, and organizational coordination. It now informs a pragmatic approach to applied AI: understanding where automation meaningfully improves decision quality and where human judgment remains decisive. In December 2025, Axako was successfully acquired, marking a 13-year founder journey that scaled the business from inception to one of Europe's leading Amazon private-label operators generating 100M+ in annual revenue across the US, EU, and China markets.