AI Product Manager

Job Summary

Total Number of Openings: 1

AI Product Manager is responsible for defining, delivering, and scaling AI-driven products that solve complex business problems and generate measurable value. This role bridges business strategy, data science, engineering, and platform teams to translate business workflows into reliable, ethical, and scalable AI solutions.

The AI Product Manager provides deep expertise in how business processes map to data, models, and AI capabilities, and how these elements can be integrated to build reusable, enterprise-grade AI products. The role serves as a subject matter expert for delivery teams and acts as a key partner for stakeholders across business, technology, governance, and leadership.

This position supports the discovery, development, and operationalization of AI/ML and GenAI solutions, including defining product vision, driving execution, measuring impact, and ensuring responsible AI practices. The ideal candidate has strong experience with AI/ML product lifecycles, cloud platforms (Azure), data-driven decision-making, and stakeholder leadership in enterprise environments.

Key Responsibilities

• Define and own AI product vision, roadmap, and success metrics aligned to business strategy and enterprise priorities.
• Experience with Generative AI and LLM-based products. Background in data science, engineering, analytics, or AI platform development.
• Identify, evaluate, and prioritize high-value AI and GenAI use cases across business domains.
• Translate business problems into clear product requirements, AI hypotheses, and acceptance criteria.
• Partner with Data Scientists, ML Engineers, Architects, and Platform teams on model selection, data readiness, performance targets, and deployment strategies
• Drive product execution from ideation and POC through production launch and continuous improvement.
• Ensure data quality, model performance, scalability, monitoring, and lifecycle management (MLOps).
• Collaborate with UX, engineering, and business stakeholders to ensure strong user adoption and value realization.
• Establish and follow responsible AI practices, including fairness, explainability, privacy, and risk management.
• Track product KPIs such as business impact, adoption, model accuracy, cost, and operational efficiency.
• Communicate product strategy, progress, and outcomes to senior leadership and executive stakeholders.
• (Lead / Principal levels) Mentor and coach other product managers and contribute to AI product best practices and standards.

Required Qualifications

• 10-20 years of product management experience with 5+ years in AI/ML products
• bachelor's degree in engineering, Computer Science, Data Science, Analytics, or a related field
• Strong understanding of AI/ML concepts including supervised and unsupervised learning, NLP, GenAI, and model evaluation.
• Experience working with data pipelines, feature engineering, model deployment, and monitoring.
• Familiarity with MLOps practices and AI product lifecycle management.
• Experience with Microsoft Azure services and cloud-based data and AI platforms.
• Understanding of APIs, microservices, and modern data architectures
• Strong product management fundamentals: discovery, roadmaps, PRDs, agile delivery, and backlog prioritization.
• Ability to define value propositions and ROI for AI initiatives.
• Strong analytical, problem-solving, and decision-making skills.
• Ability to translate complex technical concepts into clear business narratives
• Excellent communication and stakeholder management skills across technical and non-technical audiences.
• Proven ability to work effectively with global, cross-functional teams.
• Strong leadership skills with the ability to influence without authority.

Preferred Qualifications

• Experience in regulated or enterprise environments (e.g., oil gas, energy, finance, healthcare).
• Exposure to AI governance, responsible AI frameworks, and risk management practices.
• MBA or advanced degree in a related field.
• Experience scaling AI products from pilot to enterprise adoption.