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Tata Tele - Product Owner - AI Centre of Excellence

Tata Tele - Product Owner - AI Centre of Excellence

Tata Tele Business ServicesIndia
11 days ago
Job description

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

    • (ref : hirist.tech)

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