Principal AI Product Manager

SAP•Stanford, CA

2d•$198,200 - $420,000•Hybrid

About The Position

We are seeking a Principal Product Manager focused on AI/ML to join our product management organization and drive the next generation of intelligent capabilities for Spend Intelligence on SAP Business Data Cloud. In this role, you’ll serve as an AI/ML specialist, owning data enrichment end-to-end while also charting the path forward toward agentic experiences that augment existing analytics capabilities and unlock entirely new value for procurement customers. You’ll bring deep, hands-on fluency in how modern AI systems work—from LLM architectures and training pipelines to applied techniques like RAG, fine-tuning, and agent orchestration. Critically, you’ll have experience taking AI from prototype to production at scale, solving the reliability, evaluation, and operational challenges that arise when AI must perform consistently across hundreds of enterprise customers rather than hand-tuned demos. You’ll partner closely with engineering, data science, platform, UX, and field services teams to translate customer problems into AI-powered product experiences, manage roadmap dependencies across SAP Business Data Cloud, and ensure that every capability delivers measurable business value.

Requirements

Bachelor's degree or equivalent in Computer Science, Engineering, or a related technical field.
6+ years of experience in customer-facing product management
3+ years of hands-on experience building AI applications and scaling AI from prototype to production for dozens or hundreds of customers, solving challenges around reliability, evaluation, latency, cost management, and graceful failure handling.
A deep technical fluency in AI and AI system architectures, including traditional ML, LLMs, embedding models, frameworks, training pipelines, and orchestration patterns, to solve business problems at scale.
Experience defining evaluation frameworks, quality metrics, and human-in-the-loop feedback loops for AI/ML systems operating in production.
Experience building applications and agents in a B2B context, preferably for enterprise customers.

Nice To Haves

Knowledge of the analytics and/or procurement space, especially data modeling

Responsibilities

Own AI-powered data enrichment strategy and execution - define the product vision, prioritize the roadmap, and drive delivery of ML-based enrichment capabilities (e.g., spend classification, supplier normalization, anomaly detection) that operate reliably at enterprise scale within Spend Control Tower.
Design and deliver agentic capabilities - identify high-value opportunities where AI agents can augment existing analytics workflows or create entirely new product experiences; lead discovery, prototyping, and productization of these agents from zero to one to broad adoption.
Conduct deep discovery and market analysis - understand customer problems, competitive landscape, and emerging AI/ML trends to inform product strategy; translate business problems into well-scoped AI system designs that account for data availability, model reliability, and user trust.
Drive AI reliability and scale - define quality bars, evaluation frameworks, and feedback loops that ensure AI-powered features perform consistently across diverse customer environments, data volumes, and edge cases—not just curated examples.
Drive end-to-end execution and measurable outcomes - own delivery from discovery to adoption, working across both product (UX, engineering, platform) and go-to-market (product marketing, field services, sales, etc.) to ensure AI features and agents deliver clear, quantifiable business value to customers.
Shape technical direction and architectural choices - serve as the connective tissue between cutting-edge AI capabilities and business outcomes; guide engineering on system design decisions (e.g., when to apply RAG vs. fine-tuning, how to structure agent orchestration, how to balance cost vs. latency) while keeping the focus on customer value and operational viability at scale.