AI Product Owner.Injaz - Artificial Intelligence.MIT

About This Role

Key Result Areas

Product Strategy & Roadmap

- Define the vision, strategy, and roadmap for AI products in alignment with organizational goals.

- Translate business needs into AI product requirements and prioritize features based on value and feasibility.

- Continuously assess market trends, customer feedback, and emerging AI technologies to inform product evolution.

Backlog Management & Delivery

- Own and manage the product backlog, ensuring clarity, prioritization, and alignment with sprint goals.

- Collaborate with engineering and data science teams to ensure timely delivery of high-quality AI features.

- Define acceptance criteria and validate deliverables against business objectives.

Stakeholder Engagement

- Act as the primary point of contact for business stakeholders, ensuring alignment on priorities and expectations.

- Communicate product vision, progress, and outcomes to executives and cross-functional teams.

- Facilitate workshops and demos to gather feedback and drive adoption.

Governance & Compliance

Ensure AI products comply with internal governance frameworks, regulatory requirements, and responsible AI principles.

- Partner with AI Governance, Risk, and Security teams to embed controls for fairness, transparency, and explainability.

Performance & Value Realization

- Define KPIs and success metrics for AI products; monitor performance and adoption.

- Drive continuous improvement through data-driven insights and user feedback.

Knowledge, Skills and Experience

Education: Bachelor’s degree in Business, Computer Science, Data Analytics, or related field (MBA preferred).

Preferred experience:

- 8+ years in product management, with at least 3 years in AI/ML or data-driven products, or

- Management consulting background with experience in strategy, operating models, and transformation programs, or

- Startup experience in AI or emerging tech, demonstrating agility and innovation mindset.

Skills & Expertise:

- Strong understanding of AI/ML concepts, model lifecycle, and data platforms.

- Experience with Agile methodologies, backlog management tools (e.g., Jira, Azure DevOps).

- Familiarity with AI governance, compliance, and ethical AI practices.

Soft Skills: Excellent communication, stakeholder management, and ability to translate technical concepts into business value.