Product Manager, Data Ingestion & Quality (AI)

TL;DR

Product Manager, Data Ingestion & Quality (AI): Building the product foundation that transforms raw data into trusted, usable, and scalable AI training assets with an accent on data ingestion lifecycles, quality standards, and validation workflows. Focus on designing scalable platform solutions for complex data challenges, defining metadata generation strategies, and optimizing data reliability across multiple domains.

Location: Must be based in the United States

Company

An AI technology company building critical infrastructure for high-quality training data.

What you will do

• Own the product strategy and roadmap for data ingestion and quality systems to transform raw data into reliable assets.
• Define ingestion workflows, validation stages, and quality checks to create consistent standards across data sources.
• Establish product requirements for engineering teams, translating data quality challenges into scalable platform solutions.
• Lead product decisions regarding metadata generation, including tagging, confidence scoring, and schema inference.
• Develop platform-level solutions that support multiple industries while avoiding unnecessary individual customizations.
• Collaborate with engineering, data teams, and business stakeholders to align requirements and priorities.

Requirements

• 4–7 years of product management experience focused on data pipelines, data quality systems, or ingestion infrastructure.
• Proven experience transforming raw, inconsistent data into trusted and usable information.
• Strong technical fluency with the ability to write SQL, analyze pipeline outputs, and understand data architecture.
• Experience working with external data sources and complex third-party integrations.
• Ability to define product requirements for infrastructure or platform products.
• Must be based in the United States.

Nice to have

• Experience with data quality frameworks or tools such as dbt or Great Expectations.
• Familiarity with de-identification approaches for sensitive healthcare or personal enterprise datasets.
• Exposure to ML training pipelines, AI data workflows, or data governance.

Culture & Benefits

• Work on foundational technology shaping the future of AI and data infrastructure.
• High-impact role within a fast-moving and innovative environment.
• Collaborative culture centered on ownership, trust, and technical excellence.
• Environment that encourages autonomy, experimentation, and continuous learning.