We are a global company with 60+ years of experience in the automotive industry, manufacturing safe and sustainable products for people around the world. We are working for a better future where we enrich communities every day by being committed to people, innovation, and our planet. If you have what it takes to accelerate Metalsa’s vision of future mobility, we want you to join the team! For more information, visit metalsa.com. Sr AI Product Manager Position Summary We are seeking a Senior AI Product Manager – Agentic Systems to guide the agentic redesign of business processes: partnering with process owners and the AI Engineering squad to translate real workflows into agentic products that deliver measurable business outcomes. This is not another SaaS PM role: you will redesign how a leading industrial company runs its manufacturing, supply chain, and engineering processes — deciding where AI agents take over mechanical work and where humans keep the judgment, at global scale. Reporting to Innovación Co., Metalsa’s innovation organization, you will own discovery, prioritization, success metrics, and adoption, and help democratize agentic AI by enabling process owners to design and operate their own agentic solutions safely. The ideal candidate combines product management fundamentals with hands‑on experience shipping AI products to production, strong process‑redesign thinking, and the ability to translate between business stakeholders and engineering teams. Key Responsibilities Discovery & Product Strategy Lead end-to-end discovery and redesign of business processes for agentic execution: map AS-IS workflows, identify pain points and decision logic, and design TO-BE workflows where agents handle mechanical work and humans focus on judgment. Own the agentic product roadmap: prioritize workflows, decisions, and steps to agentify; balance value, risk, and feasibility; and sequence work into waves with clear baselines and kill criteria. Define success metrics for agentic products, including business outcomes, adoption, trust, and quality KPIs. Run user research and product experiments to validate hypotheses before scaling. Delivery & Engineering Partnership Partner daily with the AI Engineering squad: write product specs, define decision boundaries and human-in-the-loop checkpoints, and review evaluation results. Translate between business and engineering: turn vague business needs into clear agent specifications and turn technical constraints into business decisions. Adoption & Democratization Drive adoption with process owners and end-users through change management, training, feedback loops, and continuous iteration. Enable the democratization of agentic AI by creating playbooks, templates, and patterns that allow process owners and citizen developers to scope and operate agents safely. Governance & Communication Own the responsible AI and governance posture of agentic products, including autonomy scope, escalation rules, audit trails, and human accountability. Communicate progress and outcomes to senior leadership through monthly reviews, executive narratives, and clear value attribution. Required Qualifications Education Bachelor’s degree in Engineering, Industrial Engineering, Computer Science, Business, or a related field. Experience 7+ years of Product Management or similar experience. 2+ years shipping AI/ML or agentic products in production. Experience in complex, corporate, or industrial environments. Proven experience working with process owners, business stakeholders, and engineering teams. Demonstrated ability to drive adoption and measurable business outcomes. Required Skills Product & Process Agentic product design fundamentals: agent loops, tool use, human-in-the-loop checkpoints, and evaluation of AI quality — conceptual command matters more than specific tools. Process redesign and workflow thinking (AS-IS / TO-BE). Product discovery, user research, and experimentation. Roadmap and OKR definition. AI & Data Literacy LLM literacy and prompt design: understands what models can and cannot do, and how to specify agent behavior. SQL and data analysis for measuring outcomes. AI governance and responsible AI fundamentals. Leadership & Communication Change management and stakeholder management in enterprise environments. Executive storytelling and clear value attribution. Preferred Qualifications Domain exposure to manufacturing, supply chain, or engineering operations. Experience defining evaluation criteria for AI systems alongside engineering teams. Experience enabling citizen developers or low-code/no-code adoption programs. Experience presenting to and influencing senior executive audiences. #J-18808-Ljbffr