Director of Product

Embedding VC•San Francisco, CA

About The Position

Xnurta is an AI-native retail media and advertising optimization platform built for brands, sellers, and agencies on Amazon and beyond. We combine multi-agent AI systems, advanced predictive analytics, and deep domain expertise to deliver unparalleled advertising performance. Our platform enables both advertisers and internal experts to orchestrate custom advertising strategies—balancing automation, human insight, explainability, and control—to maximize revenue, scale operations, and maintain transparency in an increasingly complex ad ecosystem. We are seeking an exceptional Director of AI Product Management to define, drive, and scale Xnurta’s AI strategy—including model-based optimization, generative intelligence, multi-agent orchestration, predictive forecasting, and automated decision-making systems. In this role, you will lead a team of AI product managers, partner closely with engineering and data science leadership, and own the long-term vision for how AI powers every facet of the Xnurta platform. You will shape the core intelligence layer that drives automation, insights, creativity, and performance for thousands of advertisers. This is a highly strategic and highly technical leadership role—ideal for a product leader who has shipped AI/ML systems at scale and thrives at the intersection of AI strategy, systems architecture, user impact, and organizational influence.

Requirements

8–12+ years of product management experience, with significant experience in AI/ML-driven products, ad tech, or large-scale optimization platforms.
Demonstrated success shipping and scaling ML-based systems across high-volume use cases.
Strong technical understanding of ML fundamentals (training pipelines, model evaluation, offline/online experimentation, feature engineering, RL, LLM workflows, etc.).
Proven leadership experience managing PM teams and influencing cross-functional executives.
Exceptional communication and product storytelling skills—able to simplify complexity and inspire alignment.
Deep analytical mindset with fluency in data tools, metrics design, and scientific thinking.
Experience working in fast-paced SaaS, retail media, or advertising technology environments.

Nice To Haves

Experience with Amazon Ads, DSP bidding systems, MMM/MTA, predictive forecasting, or performance optimization models.
Experience deploying or integrating LLMs, agentic systems, or generative AI into production workflows.
Mandarin proficiency for cross-regional collaboration.

Responsibilities

Define and own Xnurta’s multi-year AI strategy, spanning optimization engines, agent frameworks, predictive models, attribution systems, and generative AI experiences.
Establish the vision and roadmap for AI-driven automation, intelligence, and decision-making across all product surfaces.
Identify emergent AI opportunities (LLMs, agents, reinforcement learning, causal inference, MMM/MTA, etc.) and convert them into high-leverage product initiatives.
Lead, mentor, and scale a team of AI product managers, fostering a culture of excellence, critical thinking, and rapid iteration.
Build strong partnerships with Data Science, Machine Learning Engineering, Platform Engineering, GTM, and Customer Success teams.
Align executive stakeholders around strategy, roadmaps, and critical prioritization decisions.
Partner with AI/ML leaders to define training data requirements, evaluation metrics, offline vs. online testing strategies, model deployment & monitoring standards, and model governance, explainability, and safe use.
Lead large-scale experimentation frameworks (A/B tests, simulation, offline replay, etc.).
Ensure continuous improvement of models through robust feedback loops.
Design and drive the architecture of AI-driven components such as bidding & budget optimization models, generative creative intelligence, multi-agent orchestration frameworks, spend forecasting & pacing engines, and advertiser guidance and insight-generation systems.
Work with ML engineers and architects to ensure AI components are scalable, reliable, and explainable.
Communicate AI strategy, tradeoffs, and impact clearly to executive leaders, technical teams, and customer-facing teams.
Serve as the executive-level voice of AI product across the organization.
Translate complex AI concepts into business and customer value narratives that guide GTM and operational decisions.
Ensure that AI features are intuitive, trustworthy, configurable, and aligned with advertiser needs.
Guide UX/design on interfaces that express AI decisions transparently and empower users with control.
Drive adoption and measurable business outcomes across customer segments.