[Hiring] OT Artificial Intelligence Technical Product Owner @S3 Int

Role Description

We are seeking an OT Artificial Intelligence Technical Product Owner to own the vision, roadmap and backlog for OT AI products delivered by a Buenos Aires-based product team. This role translates operational needs and prioritized use cases into a sequenced, deliverable product roadmap, ensuring AI capabilities move safely and consistently from intake and pilot into supported, measurable operational use.

The position is part of an OT Artificial Intelligence team within an OT Product Line and sets the day-to-day product direction for a cross-functional delivery team of data, machine learning, computer vision, MLOps and platform, edge integration, application development, and test and assurance engineers.

The role reports to the OT Product Line Manager and works within the architecture, standards and model lifecycle controls established by technical leadership and solution architecture. It enables OT AI priorities by converting approved use cases into reusable, secure and supportable products that business units can adopt without building isolated, one-off solutions.

The team is highly technical, creative and cross-functional. The Technical Product Owner is accountable for defining what the OT AI Product Team builds and in what order, balancing the needs of operations, engineering, data, cybersecurity, Responsible AI and business stakeholders.

Success means delivering measurable business value and adoption while maintaining safety, cybersecurity, reliability, human oversight, operator accountability and cost discipline.

Qualifications

• Bachelor's degree in Engineering, Computer Science, Information Systems, Data Science or a related field, or equivalent experience.
• Six or more years of experience delivering technology solutions in industrial, operational technology, data or AI environments, including at least three years as a Product Owner, Product Manager or Technical Lead.
• Demonstrated experience owning a technical product backlog and roadmap within an Agile delivery environment such as Scrum or SAFe.
• Experience writing epics, features and user stories with clear acceptance criteria and nonfunctional requirements using Azure DevOps or comparable tools.
• Working understanding of AI and machine learning delivery, including data requirements, model training and evaluation, deployment, monitoring, drift and retraining.
• Ability to discuss computer vision, time-series analytics, generative AI and AI-enabled application use cases in sufficient depth to guide engineers and challenge assumptions.
• Understanding of OT environments and constraints, including safety, availability, network segmentation, constrained or disconnected connectivity and controlled change.
• Working knowledge of OT cybersecurity concepts, including the Purdue reference model and ISA/IEC 62443 zones and conduits, and Responsible AI principles.
• Experience leading delivery with distributed teams and stakeholders across countries and time zones.
• Experience defining success metrics, tracking business value and making evidence-based prioritization and trade-off decisions.
• Fluent written and spoken English, with the ability to communicate priorities, risks and decisions clearly to engineers, operators, cybersecurity reviewers and business sponsors.

Requirements

• Own the OT AI product vision, strategy and roadmap for assigned products, aligned with organizational priorities and business unit needs.
• Build, refine and prioritize the OT AI product backlog in Azure DevOps, writing clear epics, features and user stories with measurable acceptance criteria, nonfunctional requirements and definitions of done.
• Partner with product managers, program managers and use-case sponsors to qualify intake, confirm fit with the product roadmap, avoid duplication and sequence new work against committed delivery.
• Translate operational problems, value hypotheses and customer feedback into product requirements, success metrics and release plans the engineering team can execute.
• Lead PI planning, sprint planning, backlog refinement, sprint reviews and demos; accept completed work and communicate progress, risks and dependencies to technical leadership and stakeholders.
• Ensure products follow established AI reference architectures, guardrails, deployment standards and model lifecycle controls.
• Guide products through pilot-to-production stages, including intake and qualification, design and pilot readiness, controlled pilot, production readiness and handoff, and ongoing operation, change or retirement.
• Coordinate required reviews and approvals, including architecture, cybersecurity, applicable corporate policies, Responsible AI, data governance and site change management.
• Define the intended autonomy level for each product (advisory, human-approved, bounded automation or autonomous) and ensure human oversight, fallback, rollback and operator accountability requirements are captured in the backlog.
• Coordinate dependencies with existing OT delivery teams, platform owners, vendors and partner organizations so parallel efforts converge on shared, reusable capabilities.
• Define product success measures and track value delivered, including adoption, production model performance, operational impact, support burden and cost.
• Establish the operational handoff for each product, including named service and site owners, support runbooks, incident response, monitoring and retirement criteria.
• Maintain product records in the AI product catalog and enterprise AI inventory, keeping documentation, decision logs and release notes current.
• Provide product input to business planning and funding cycles, including effort estimates, licensing and consumption costs, business case inputs, and potential impacts on committed work.

Company Description