AI Platform Product Manager

Walmart Global Tech's presence in Israel has grown over the past few years through 4 acquisitions to date, and this team sits at the core of Walmart's e-commerce platform — the largest retailer in the world.

The Item Intelligence Platform is the intelligence layer behind item-level insights at global e-commerce scale — applying advanced Data Science, NLP, ML, and LLM-based capabilities to infer deep product insights. One flagship capability alone serves over 240 million sessions daily. The platform stands on three pillars: Discoverability, Platform Federation, and Capabilities Evaluation (the authoritative quality stamp).

Your Mission:



You bridge complex technical infrastructure and data-science-driven capabilities — understanding the DS and Data Engineering spectrum deeply enough to shape what the platform serves, how it serves it, and what quality means before anything reaches a downstream consumer. You identify the common platform needs underneath diverse requests and translate them into a unified, scalable roadmap.

Responsibilities:

• 2–4 years of PM or Technical PM experience in backend, platform, API, or data-driven environments.
• Strong ability to abstract specific feature requests into generalized, reusable platform capabilities.
• A B.Sc. in Computer Science, Software Engineering, or a related technical/quantitative field — or meaningful equivalent experience.
• Deep comfort with technical systems: REST APIs, databases, ETL pipelines, and high-scale data infrastructure. Strong conceptual grasp across the stack (Kafka, NoSQL, BigQuery, agentic/MCP platforms, and similar).
• Bias for action — extremely organized, execution-focused, and eager to move fast in ambiguity.
• Professional working proficiency in English (spoken and written) — fluent enough to own async communication, lead cross-timezone meetings, and write precise technical specs with a global team.
  
  

• B2C e-commerce or consumer product background — consumer intuition helps prioritize the right platform signals.
• Hands-on experience working alongside Data Science on model evaluations or quality frameworks.
  
  

• Are genuinely excited by the challenge of building infrastructure that scales to hundreds of millions of shoppers — even when the work itself is invisible to them.
• Learn fast, share ideas openly, and give honest feedback.
• Have a can-do attitude and thrive in ambiguous, fast-moving environments.
• Think in systems — connecting a single technical decision to its impact across every team and surface it touches.