AI Product Owner

Role Overview

As an AI Product Owner, you will be the strategic bridge between business stakeholders, data scientists, engineers, and end users. You will own the product lifecycle for AI-powered solutions—ranging from computer vision and NLP to intelligent automation—ensuring they deliver measurable business impact, scalability, and seamless integration into enterprise workflows.

Key Responsibilities

• Product Strategy & Vision: Define and execute the product roadmap for AI-driven enterprise solutions, aligning with business goals and market trends (e.g., AIaaS, intelligent claim processing, autonomous workflows).
• Stakeholder Collaboration: Partner with enterprise clients (e.g., insurers, ITAD providers, software vendors) to identify pain points, gather requirements, and translate them into actionable product features.
• AI Solution Ownership: Own end-to-end delivery of AI products—from ideation and prototyping to deployment and post-launch optimization—leveraging frameworks like Ai Fabric, LLM-agnostic architectures, and AWS-based inference pipelines.
• Cross-functional Leadership: Work closely with AI/ML engineers, data scientists, UX designers, and DevOps teams to prioritize backlog, refine user stories, and ensure high-quality delivery using Agile/Scrum practices.
• Value Delivery Measurement: Define KPIs (e.g., 30% reduction in processing time, 99.98% accuracy in damage detection) and track ROI using tools like Power BI, Jira, and Azure DevOps.
• Innovation & Scalability: Drive productization of AI capabilities (e.g., damage detection models, agent assistants) into reusable, tenant-configurable components for multi-client deployment.
• Governance & Compliance: Ensure all AI products adhere to ethical AI principles, data privacy standards (GDPR, CCPA), and enterprise security protocols.
• Market & Competitive Insight: Monitor emerging AI trends, competitive landscapes, and client feedback to continuously evolve the product offering.

Qualifications & Skills

• Education: Bachelor’s or Master’s in Computer Science, Engineering, Business Analytics, or related field.
• Experience: 6 - 8 years product management, preferably in AI/ML, software engineering, or enterprise SaaS products. Experience in generative AI, computer vision, or enterprise automation is a strong plus.
• Technical Proficiency:
  • Familiarity with AI/ML concepts (e.g., neural networks, model training, inference pipelines).
  • Understanding of cloud platforms (AWS, Azure), APIs, and CI/CD pipelines.
  • Experience with AI platforms like TensorFlow, TFServing, or similar.
• Soft Skills:
  • Exceptional communication and presentation skills.
  • Strong analytical thinking and problem-solving abilities.
  • Ability to influence without authority across technical and non-technical teams.
  • Customer-centric mindset with a focus on business outcomes.
• Certifications (Preferred): Certified Scrum Product Owner (CSPO), PMI-ACP, or AI-specific certifications (e.g., AWS AI/ML).