Job description

DIRECTOR OF AI PRODUCT MANAGEMENT WHO WE ARE 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. OUR VALUES - Humble Excellence – Lead with humility, execute with mastery. - Always Learning – AI evolves fast; so do we. - Extreme Accountability – Own outcomes end-to-end. - Diverse Thinking – Cross-industry, cross-domain perspectives fuel innovation. - Customer Obsession – Every model, feature, and insight must create tangible value for advertisers. POSITION OVERVIEW 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. KEY RESPONSIBILITIES AI STRATEGY & VISION - 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. LEADERSHIP & TEAM BUILDING - 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. MODEL & DATA LIFECYCLE LEADERSHIP - Partner with AI/ML leaders to define: - training data requirements - evaluation metrics - offline vs. online testing strategies - model deployment & monitoring standards - 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. AI SYSTEM DESIGN & PRODUCT ARCHITECTURE - 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 - advertiser guidance and insight-generation systems - Work with ML engineers and architects to ensure AI components are scalable, reliable, and explainable. CROSS-FUNCTIONAL INFLUENCE - 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. CUSTOMER IMPACT & ADOPTION - 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. QUALIFICATIONS REQUIRED - 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. PREFERRED - 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. WHAT WE OFFER - Competitive salary and benefits - A supportive and inclusive AI-first culture - Unlimited PTO - The opportunity to build the future of AI-driven retail media alongside industry-leading talent

Requirements

Must-haves

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.
training data requirements
evaluation metrics
offline vs. online testing strategies
model deployment & monitoring standards
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
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.

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningllm

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Vision

Pto