Product Owner, Artificial Intelligence

Overview

As Product Owner for Evergreen.AI, you will guide the vision, roadmap, and delivery of the Agent Foundry Data Platform. This platform supports the core mission of Evergreen.AI, which is to incubate, deliver, and scale real world agentic AI solutions. Your work will help teams build enterprise ready systems that combine agents, workflows, knowledge pipelines, evaluations, and secure cloud deployment. You will translate business needs into clear product direction, maintain a healthy backlog, and partner with architects, engineers, and AI specialists to move work from concept into production.

Responsibilities

Product Ownership and Strategy

• Define the product vision and roadmap for the Agent Foundry Data Platform.
• Translate customer conversations, business goals, and user problems into clear priorities.
• Connect the roadmap to the broader mission of Evergreen.AI.

• Own the product backlog and write simple, clear, and detailed user stories.
• Prioritize features based on business value, user impact, and technical effort.
• Lead sprint ceremonies in a collaborative way.

• Work with executives, engineers, delivery teams, and users to understand requirements.
• Share updates, risks, and tradeoffs in a clear and honest manner.
• Represent the voice of the customer and keep teams aligned.

• Track KPIs, usage, adoption, and performance.
• Ensure features meet security, scalability, compliance, and reliability standards.
• Support production readiness through documentation and validation.

• Encourage positive teamwork and open communication.
• Approach challenges with curiosity and resilience.
• Foster a culture of learning and improvement.

• Bachelor's degree in Computer Science, Engineering, Information Systems, Business with a technology focus, or equivalent experience.
• 5+ years as a Product Owner or Product Manager.
• Experience delivering SaaS platforms, AI or machine learning products, or enterprise data systems.
• Familiarity with Agile and Scrum practices and tools like Azure DevOps or Jira.
• Strong understanding of cloud technologies, with preference for Azure.
• Clear communication skills and ability to work across diverse stakeholders.
• Comfort working with architects and engineers in technical discussions.

• Master's degree such as an MBA or graduate degree in CS, IS, Data, or Technology Management.
• Background in AI, machine learning, synthetic data, or data platforms.
• Experience with Microsoft Azure AI and DevOps pipelines.
• Product management certifications such as CSPO or Pragmatic.
• Familiarity with multi agent systems, evaluation frameworks, or knowledge pipelines.