Position Title : Product Owner - AI Centre of Excellence (CoE)

Reporting To : Head - AI CoE

Location : Any

Industry : Telecom & Cloud Services

Qualifications :

- Masters Bachelors in Computer Science, Data Science, or related field.

- 10+ years of experience in data, analytics, or AI leadership roles.

- 3+ yrs of relevant experience AI experience.

- Proven track record in delivering AI/ML solutions at scale.

- Deep understanding of AI governance, MLOps, and responsible AI practices.

- Strong leadership and stakeholder management skills.

- Excellent communication and change management capabilities.

- Product Owner certification (i.e., CSPO, SAFe POPM) preferred.

- Familiarity with telecom BSS/OSS or cloud platforms is a plus.

Job Summary :

To act as the voice of the customer and business within the AI CoE, defining and prioritizing product requirements, coordinating with cross-functional teams, and ensuring that AI/ML products deliver tangible business value.

The Product Owner plays a crucial role in shaping the roadmap and execution of AI/analytics initiatives in telecom and cloud domains.

Key Responsibilities :

- Own the product vision, roadmap, and backlog for assigned AI/ML or analytics products.

- Gather and refine requirements from business stakeholders, domain SMEs, and users.

- Collaborate with data scientists, engineers, and UI/UX teams to develop high-quality deliverables.

- Prioritize features and user stories based on business impact, value, and dependencies.

- Conduct sprint planning, backlog grooming, and user acceptance testing (UAT).

- Drive continuous feedback loops with users to refine and enhance the product.

- Ensure alignment with AI CoE governance, data privacy, model explainability, and operationalization standards.

- Prepare product demos, training, and documentation for effective rollout and adoption.

- Track KPIs such as accuracy, adoption, ROI, and user satisfaction for AI solutions.

Objectives :

- Accelerate AI-driven transformation and innovation.

- Maximize ROI from AI investments through strategic alignment and execution.

- Promote widespread AI adoption across business units.

- Ensure responsible, explainable, and secure AI usage.

Key Result Areas (KRAs) :

- Number and impact of AI use cases deployed.

- AI adoption rate and cross-functional engagement.

- Accuracy, reliability, and relevance of deployed models.

- Compliance with AI governance and ethical standards.

- Training hours and AI upskilling metrics across the organization.

Expected Outcomes :

- Scalable and reusable AI solutions across the enterprise.

- Improved decision-making and operational efficiency.

- Tangible business advantage through applied AI innovation.

- Strong AI governance and minimized risk exposure.

Key Competencies :

- Product Thinking & Business Value Orientation

- Agile Delivery & Stakeholder Management

- Technical Curiosity & AI Awareness

- Communication & Storytelling with Data

- Cross-functional Collaboration