Lead Product Manager AIOPs

About the Role: Grade Level (for internal use): 11The Team: The AIOps team is responsible for S&P Global's enterprise AIOps platform and strategy, driving the modernization of IT Operations and Site Reliability Engineering (SRE) through intelligent observability, event intelligence, automation, and AI-driven insights. DTS Platform & Tools – Service Enablement: We serve as thought leaders in AIOps, partnering across IT Operations, SRE, engineering, infrastructure, service management, and application teams to solve enterprise operational challenges. Our mission is to improve reliability, reduce operational complexity, optimize technology investments, and enable more proactive and resilient technology operations by applying AI. Responsibilities and Impact: Own and execute the AIOps product roadmap, aligning priorities with enterprise reliability goals, operational maturity, adoption targets, and measurable business outcomes. Translate operational needs into clear product requirements, use cases, user stories, acceptance criteria, and prioritized backlog items across the AIOps product lifecycle. Ownership of high-impact AIOps capabilities, including noise reduction, event management, correlation, anomaly detection, root cause analysis, predictive alerting, and self-healing remediation. Partner across Operations, infrastructure, SRE, platform engineering, service management, application teams, security, and vendors to operationalize AIOps capabilities and drive adoption at enterprise scale. Define and track success metrics for alert quality, incident reduction, MTTD, MTTR, service health, automation coverage, platform adoption, and operational efficiency. Present roadmap progress, risks, decisions, and outcome metrics to senior stakeholders to influence improvements to tooling, workflow, and the operating model. Analytical and data-driven mindset with strong problem-solving, prioritization, and decision-making skills. What We’re Looking For: Basic Required Qualifications: 10+ years of experience in product management, IT operations, SRE, observability, platform engineering, or related enterprise technology roles. Strong understanding of AIOps concepts, including event correlation, anomaly detection, root cause analysis, noise reduction, predictive analytics, and automated remediation. Experience defining product roadmaps, managing requirements and backlog priorities, and delivering technical platform capabilities across the product lifecycle. Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience. Machine Learning: Expertise in time-series forecasting, clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure components Additional Preferred Qualifications: