OverviewWe are seeking a Digital Product Sr Manager Intelligent Vision to define, build, and scale PepsiCo's Vision based digital products as a global capability supporting intelligent automation, quality assurance, safety, asset monitoring, and operational excellence across manufacturing plants, warehouses, and distribution centers.
This role will own the product vision, roadmap, and feature backlog for Intelligent Vision, enabling enterprise-scale computer vision and artificial intelligence capabilities that transform visual information into actionable business intelligence. The Vision based digital product/s provide standardized AI-powered inspection, quality monitoring, safety analytics, inventory visibility, asset recognition, process compliance, and intelligent event detection capabilities that enhance operational performance while reducing manual effort.
The Product Owner will work closely with Quality, Manufacturing, Supply Chain, Engineering, Data Science, AI Engineering, solution architects, software development teams, and strategic technology partners to deliver scalable computer vision products that accelerate AI adoption across PepsiCo's global manufacturing and logistics network
ResponsibilitiesIntelligent Vision Product Strategy
- Own the vision, strategy, and multi-year roadmap for PepsiCo's Intelligent Vision products supporting manufacturing, warehousing, quality, safety, and logistics operations.
- Define scalable computer vision capabilities that can be deployed consistently across PepsiCo's global manufacturing and distribution network.
- Identify high-value AI vision use cases and prioritize investments based on business value, operational impact, and scalability.
- Partner with Quality, Manufacturing, Supply Chain, Safety, and Digital organizations to develop enterprise vision capabilities.
- Establish measurable product outcomes tied to quality improvement, safety performance, labor efficiency, and operational excellence.
Intelligent Vision Products & Capabilities
- Own the roadmap for AI-enabled visual inspection, quality monitoring, safety analytics, asset recognition, inventory visibility, process compliance, and intelligent event detection.
- Define reusable AI models, vision pipelines, synthetic data strategies, and computer vision frameworks that accelerate deployment globally.
- Drive standardization of edge AI, camera infrastructure, inference pipelines, and model lifecycle management.
- Enable integration of computer vision outputs into Operational Twins, Engineering Twins, enterprise analytics platforms, and AI services.
- Establish governance processes ensuring model accuracy, explainability, scalability, and continuous learning.
Product Ownership & Agile Delivery
- Own the Intelligent Vision product backlog, roadmap, release planning, and feature prioritization.
- Translate customer requirements into user stories, acceptance criteria, and product releases.
- Partner with AI engineers, data scientists, software developers, UX teams, and infrastructure teams throughout Agile delivery.
- Balance innovation with reliability, scalability, cybersecurity, and operational readiness.
- Ensure continuous improvement of Vision products through customer feedback and AI model performance monitoring.
Platform Integration & Cross-Functional Collaboration
- Ensure Intelligent Vision products integrate seamlessly with the Digital Twin Platform and complementary products including Spatial, Engineering, and Operational Twins.
- Collaborate with Platform Engineering, AI Centers of Excellence, Data Engineering, Manufacturing Engineering, and Warehouse Operations teams.
- Partner with external AI vendors, camera providers, robotics companies, and system integrators to align product roadmaps.
- Promote reusable data products, AI services, APIs, and platform capabilities that enable enterprise-wide adoption.
User Experience & Business Value
- Define user personas for quality inspectors, plant operators, warehouse associates, safety managers, manufacturing engineers, and operations leaders.
- Establish KPIs measuring inspection accuracy, defect detection, safety improvements, automation rates, model performance, and business value.
- Conduct product demonstrations, user testing sessions, and stakeholder workshops to continuously refine the product experience.
- Drive global adoption through standardized deployment playbooks, training, documentation, and change management.
Compensation & Benefits:
- The expected compensation range for this position is between $140,100 - $234,850.
- Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
- Bonus based on performance and eligibility target payout is 15% of annual salary paid out annually.
- Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
- In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.
QualificationsEducation- Bachelor's degree required in Computer Science, Artificial Intelligence, Electrical Engineering, Robotics, Data Science, Industrial Engineering, or related field.
- Master's degree preferred in Artificial Intelligence, Machine Learning, Computer Vision, Engineering, or Business Administration.
Experience- 10+ years of experience in Product Management, Artificial Intelligence, Computer Vision, Manufacturing Technology, or Digital Transformation.
- Proven experience managing AI-enabled enterprise software products from strategy through deployment.
- Experience delivering Computer Vision or Machine Learning solutions within manufacturing, logistics, or industrial environments.
- Experience working with Agile software development teams and AI engineering organizations.
- Experience balancing innovation with enterprise scalability, governance, and operational deployment.
Technical Expertise- Strong understanding of Computer Vision, Machine Learning, Deep Learning, and AI model lifecycle management.
- Experience with industrial camera systems, edge computing, AI inference platforms, and intelligent automation.
- Familiarity with synthetic data generation, MLOps, model governance, and AI deployment at scale.
- Understanding of Digital Twin platforms, cloud-native architectures, APIs, and enterprise integration.
- Knowledge of manufacturing quality systems, warehouse operations, robotics, automation, and industrial AI applications.
Leadership- Strong product management and strategic planning capabilities.
- Excellent communication skills with the ability to influence senior technology and business leaders.
- Proven ability to lead highly technical cross-functional teams.
- Strong customer-centric mindset focused on delivering measurable business outcomes.
- Demonstrated success driving enterprise AI adoption within global organizations.
Success Metrics
- Intelligent Vision capabilities deployed successfully across prioritized manufacturing plants and warehouse operations globally.
- Increased automation of quality inspection, safety monitoring, inventory recognition, and operational analytics through reusable AI products.
- Significant improvements in defect detection, inspection accuracy, safety compliance, and operational efficiency.
- Standardized enterprise Computer Vision capabilities supporting multiple business functions through reusable AI services.
- High AI model accuracy, scalability, reliability, and operational adoption across global deployments.
- Product roadmap delivered on schedule with measurable customer adoption and business value realization.
- Strong collaboration across AI, Platform, Manufacturing, and Operations teams resulting in scalable enterprise Intelligent Vision capabilities.
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