Product Manager

Who We Are
Xnurta, powered by SparkX, 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 looking for an AI Product Manager who can bridge user needs, data science, engineering, and business strategy to build the next generation of AI-powered ad optimization, insights, automation, and decision systems at Xnurta.
You will be responsible for shaping AI-driven features—from model-based recommendations and optimizations to multi-agent workflows, reporting intelligence, and generative UX experiences.
This role is ideal for someone who loves working at the intersection of ML models, data, product design, and real customer outcomes.
Key Responsibilities
AI Product Strategy & Vision

Define and drive the roadmap for AI-powered features, including prediction models, optimization engines, scoring systems, and insight-generation workflows.
Translate complex customer problems into machine-learning opportunities, balancing automation with human-in-the-loop control.
Partner with ML engineers, data scientists, and UX to design explainable, trustworthy AI behavior.
Cross Functional Leadership

Work closely with engineering, data science, design, and operations teams to deliver high-quality AI systems.
Align stakeholders across business, GTM teams, and leadership through clear product frameworks, metrics, and storytelling.
Drive feature feasibility discussions including algorithmic tradeoffs, data availability, and model performance constraints.
Model & Data Lifecycle Leadership

Collaborate with data science to define data requirements, training pipelines, evaluation metrics, and model success criteria.
Lead experiments (A/B tests, multi-arm bandits, offline evaluation) to assess model impact and improve performance.
Establish feedback loops between users, models, and product outcomes to enhance long-term model accuracy and reliability.
User Experience & Adoption

Ensure AI capabilities are intuitive, reliable, and transparent for advertisers and internal teams.
Create interfaces, workflows, and explanations that build trust in AI recommendations.
Balance automation with the right levels of configurability, guardrails, and override controls.
Product Execution

Own PRDs, specs, user stories, and acceptance criteria for AI-driven features.
Prioritize roadmap based on customer impact, data opportunity, technical feasibility, and strategic alignment.
Monitor product and model performance using metrics such as lift, accuracy, ROI, adoption, latency, and customer satisfaction.
Qualifications
Required

Bachelor’s degree in Computer Science, Engineering, AI/ML, Business, or related field.
2–5 years of product management experience, ideally in AI/ML, Ad Tech, Martech, analytics, or optimization systems.
Demonstrated ability to ship data-driven or ML-driven products end-to-end.
Strong understanding of concepts such as:
model training & evaluation
prediction systems
optimization logic (bidding, pacing, budget allocation, LTV, etc.)
data pipelines & feature engineering
experimentation frameworks
Experience working within Agile/Scrum with engineering and data science teams.
Strong communication and storytelling skills, especially when explaining complex AI decisions to non-technical stakeholders.
Analytical mindset with experience using SQL, dashboards, or data analysis tools.
Preferred

Experience with retail media, Amazon Ads, DSP platforms, or marketing AI.
Familiarity with generative AI, LLMs, agentic workflows, or retrieval-augmented systems.
Experience designing trust & safety, explainability, or model-governance features.
Mandarin proficiency preferred 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
JOB CODE: 1000064