Senior AI Product Owner - R01566192
Role details
Job location
Tech stack
Job description
Product Ownership & Delivery
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Own the product backlog, roadmap, and sprint priorities for AI and analytics initiatives.
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Translate business needs into detailed user stories, acceptance criteria, and product requirements.
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Drive sprint planning, backlog grooming, demos, and release readiness.
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Ensure predictable delivery, quality outcomes, and alignment with client priorities.
AI & Analytics Enablement
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Lead AI-enabled use cases including:
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Predictive and operational analytics
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Machine Learning solutions
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Computer Vision (drawings, images, site inspections)
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Document intelligence, OCR, and GenAI / LLM-based applications
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Collaborate closely with data science and engineering teams on solution design, experimentation, and production deployment.
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Support AI lifecycle governance, performance tracking, and continuous improvement.
Construction Domain Engagement
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Work onsite with client stakeholders across construction operations, estimation, procurement, and project delivery.
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Apply construction domain context to shape meaningful AI and analytics features.
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Leverage Division 8 knowledge (doors, frames, hardware, glazing, access systems) where applicable to inform product decisions.
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Bridge communication between construction SMEs and technical delivery teams.
Client & Stakeholder Management
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Act as the primary onsite point of contact for product-related discussions.
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Facilitate workshops, requirement discussions, and solution walkthroughs.
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Provide regular updates on progress, risks, and dependencies to client leadership.
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Coordinate effectively with offshore and near-shore delivery teams.
Requirements
Do you have experience in Technical product management within tech?, * 8-12+ years of overall experience across product management, analytics, AI/ML, or enterprise technology delivery.
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4-6+ years of experience as a Product Owner or Product Manager for data- or AI-driven products.
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Proven experience working onsite with US clients, preferably in consulting or enterprise delivery environments.
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Early-career hands-on experience in analytics, data engineering, data science, or software engineering.
Technical Skills
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Strong understanding of:
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AI/ML concepts and solution lifecycles
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Analytics platforms and data ecosystems
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Cloud platforms (GCP, Azure, or AWS)
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APIs, data pipelines, and system integrations
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Ability to translate technical concepts into clear business-focused outcomes.
Good to Have / Preferred
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Experience in the construction or built-environment industry.
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Division 8 domain knowledge (doors, frames, hardware, glazing systems).
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Exposure to ConTech platforms, BIM/CAD workflows, or blueprint/document analytics.
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Experience applying Computer Vision or GenAI in industrial or operational settings.
Band C Expectations
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Strong individual contributor with end-to-end ownership of product delivery.
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Comfortable working independently in an onsite client environment.
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Hands-on in backlog management, requirement definition, and stakeholder engagement., * Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Analytics, or related field.
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Product management or agile certifications (CSPO, SAFe POPM, etc.) are a plus.