AI Product Owner AD & SM Level

About the Role

We’re looking for an AI Product Owner to lead the delivery of AI-powered products and features from machine learning models to generative AI and LLM-based applications. You’ll connect business goals user needs and technical teams making sure we build AI solutions that are valuable responsible and shipped on time. You’ll own the product backlog define what “good” looks like for AI outputs and work closely with data scientists ML engineers designers and stakeholders.

Key Responsibilities

Product ownership

• Own and prioritize the product backlog for AI initiatives balancing business value feasibility risk and effort
• Translate business problems into clear user stories acceptance criteria and success metrics
• Define the product vision and roadmap for AI features in partnership with the Product Manager and leadership
• Run sprint planning backlog refinement and reviews with the delivery team

AI-specific delivery

• Identify and validate high-impact AI use cases including build vs. buy vs. fine-tune decisions
• Define evaluation criteria for model performance (accuracy relevance latency cost hallucination rate bias)
• Work with data teams to ensure data availability quality labeling and governance
• Plan for the full AI lifecycle: experimentation deployment monitoring retraining and iteration
• Design human-in-the-loop workflows and fallback behaviors where model confidence is low

Stakeholder collaboration

• Act as the bridge between technical teams and non-technical stakeholders explaining AI capabilities and limitations in plain language
• Manage expectations around what AI can realistically deliver
• Gather feedback from users and stakeholders and turn it into product improvements

Responsible AI and governance

• Partner with Legal Security and Compliance on privacy IP and regulatory requirements (e.g. GDPR EU AI Act India’s DPDP Act)
• Embed responsible AI practices: fairness transparency explainability and safety testing
• Maintain documentation such as model cards risk assessments and usage policies

Performance and value tracking

• Define and track KPIs such as adoption user satisfaction task success rate cost per query and ROI
• Run A/B tests and pilots to validate impact before scaling

Required Qualifications

• 10-15 years of experience in product ownership product management or business analysis with at least 1–2 years on AI/ML or data-driven products
• Working knowledge of AI/ML concepts: supervised and unsupervised learning NLP LLMs prompt engineering RAG and model evaluation
• Strong experience with Agile/Scrum methodologies and tools such as Jira Azure DevOps or Confluence
• Proven ability to write clear requirements and prioritize in ambiguous fast-changing environments
• Excellent communication and stakeholder management skills
• Analytical mindset with comfort in metrics dashboards and experimentation
• Bachelor’s degree in computer science Engineering Business or a related field

Preferred Qualifications

• Hands-on experience launching generative AI or LLM-powered products
• Familiarity with cloud AI platforms (Azure AI AWS Bedrock/SageMaker Google Vertex AI) and APIs from model providers
• Basic SQL or Python skills for data exploration
• Experience with MLOps concepts such as CI/CD for models monitoring and drift detection
• Certifications such as CSPO/PSPO or AI/ML product certifications
• Master’s degree or MBA

Key Competencies

• Customer and outcome focus
• Systems and critical thinking
• Technical fluency without needing to be a engineer
• Ethical judgment and risk awareness
• Influencing without authority
• Curiosity and continuous learning in a rapidly evolving field