time-to-impact + Define product hypotheses, evaluation criteria, and trust thresholds for AI capabilities (e.g., accuracy, containment, correction rates, explainability, user confidence) + Partner with Architecture, Data, and Engineering to shape feasible AI solutions that meet business intent, Responsible AI requirements, and operational constraints—without owning technical design + Own adoption and behavior-change strategy for AI products, incorporating rollout feedback, user corrections, and realized outcomes into roadmap evolution + Establish and operate autonomy governance with Responsible AI, Legal, Risk, and Operations to determine when AI may act, advise, or must defer to human approval + Lead and develop Product Managers, strengthening AI product craft across outcome definition, HITL design, evaluation planning, and risk stewardship + Communicate product status, risks, and performance using AI-relevant evidence, including adoption, trust signals, correction rates, cost per interaction, and value realization **Qualifications** **Minimum Qualifications** + Bachelor's Degree plus at least 12 years of product management experience, including demonstrated ownership of AI-enabled or decision-automation outcomes, and at least 4 years in a product leadership role, or demonstrated equivalent experience and education + Proven experience owning outcomes for AI-enabled products, including autonomy decisions, adoption strategy, and measurable business impact + Strong ability to translate business problems into AI-ready product definitions, including intents, guardrails, evaluation plans, and human-AI workflows + Demonstrated judgment balancing AI value, risk, trust, and cost under real-world constraints + Excellent communication and stakeholder influence skills across Product, Responsible AI, Architecture, Data, Operations, and Legal **Preferred Qualifications** + Direct experience defining autonomy levels, HITL policies, and Responsible AI requirements for production systems + Familiarity with agentic workflows, RAG-based experiences, AI evaluation frameworks, and observability metrics from a product ownership perspective + Experience establishing AI success measures such as containment, correction rates, explainability, bias controls, and user trust + Fluency collaborating with architects and engineers on AI constraints (data readiness, model risk, cost/quality trade-offs) without owning technical implementation + Track record driving behavior change and adoption for AI capabilities in regulated, high-risk, or mission-critical environments + Experience operating in federated or matrixed product and delivery models, with strong focus on value realization and continuous learning loops **Additional Information** + Relocation assistance is not available for this position + Sponsorship for US work authorization is not available for this position, now or in the future. We invite you to bring your bold ideas and big dreams and become part of a global team of over 50,000 planners, designers, engineers, scientists, digital innovators, program and construction managers and other professionals delivering projects that create a positive and tangible impact around the world.