Senior Technical Product Owner - Data and AI

About Boeing Vancouver

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Boeing Vancouver is seeking a Senior Technical Product Owner - Data and AI, reporting to the Senior Manager – AI & Analytics. The role is based out of the Richmond BC office.

This role requires deep technical expertise in data technologies, AI, agentic architecture, and knowledge graphs, combined with strong technical product ownership skills to enable the development of value creating data products and AI capabilities.

Position Responsibilities

• Own the end-to-end product lifecycle for data-driven AI products, with a focus on data products, agentic systems and knowledge graph technologies.
• As part of the data science team, collaborate closely with product development, engineering and architecture teams to define technical requirements, system design, and capability features.
• Translate complex technical concepts into actionable user stories and acceptance criteria.
• Prioritize and manage the product backlog, balancing technical debt, feature development, and innovation.
• Act as the technical liaison between data science, engineering, and business teams to ensure alignment and clear communication.
• Drive agile ceremonies, including sprint planning, backlog grooming, and retrospectives, with a technical perspective.
• Monitor data product and model performance, data quality, and system scalability to inform continuous improvement.
• Stay current with emerging technologies in AI, agentic architectures, and knowledge graphs to guide product strategy and innovation.

Basic Qualifications (Required Skills/Experience)

• 3+ years of experience in technical product management or product ownership, specifically in data science, AI, data products, or related technical domains.
• 4+ years of experience designing, developing & optimizing AI/ML solutions, data science workflows, and analytics methodologies.
• 3+ years of experience leading effectively with cross-functional teams.
• 3+ years of experience working in agile environments, with a foundational understanding of agile principles and practices.
• 3+ years of experience leveraging analytical and problem-solving skills to monitor data science and AI model performance and inform improvements.
• 3+ years of experience in writing clear and concise technical requirements and user stories.
• Must be legally able to work in Canada.
• Individuals must not pose a risk for safeguarding of controlled goods.
• Must be eligible to handle US export-controlled data.

Preferred Qualifications (Education/Experience)

• Strong technical background with hands-on understanding of data mesh technologies, data structures, APIs, cloud capabilities, AI models, agentic architecture, and knowledge graph technologies.
• Experience working closely with engineering and data science teams in agile environments.
• Bachelor’s or master’s degree in Computer Science, Engineering, Data Science, or a related technical field preferred.
• Experience in managing stakeholder expectations and facilitating discussions to align product vision and priorities.
• Exceptional verbal and written communication skills, with the ability to convey complex ideas clearly and persuasively to both technical and non-technical audiences.
• Experience in creating and delivering presentations to various stakeholders, including senior executive leadership and external partners.
• Experience in coaching and mentoring team members, fostering a culture of continuous learning and improvement.
• Experience in developing and communicating a clear vision and roadmap that resonates with stakeholders.

Additional Information

This requisition is for a locally hired position in Canada. The employer is Boeing Canada. Candidates must be legally authorized to work in Canada. Benefits and pay are determined by Canada and are not on Boeing US-based payroll. This is not an expatriate assignment.

Salary pay range - $94,000.00 - $167,000.00 CAD

Key skills/competency

• Data Technologies
• AI/ML Solutions
• Agentic Architecture
• Knowledge Graphs
• Product Ownership
• Agile Methodologies
• Data Science
• Technical Requirements
• System Design
• Data Quality Monitoring