Lead Product Manager AIOPs

Overview

Lead Product Manager for the AIOps team, which owns S&P Global's enterprise AIOps platform and strategy to modernize IT Operations and Site Reliability Engineering through observability, event intelligence, automation and AI-driven insights.

What you'll do

• 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 product requirements, use cases, user stories, acceptance criteria and prioritized backlog items across the AIOps product lifecycle.
• Own 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.

What you'll need

• 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.

Nice to have

• Experience with enterprise observability and AIOps platforms such as ServiceNow ITOM, Splunk, Dynatrace, Datadog, BigPanda, New Relic or similar platforms.
• Familiarity with cloud-native platforms, container orchestration systems, distributed systems, service mapping and telemetry standards.
• Experience defining KPIs, SLOs, product adoption measures and operational maturity frameworks for enterprise reliability and service performance.
• Relevant certifications in product management, cloud, ITSM, observability, Agile or platform engineering are a plus.

Details

• Location: Hyderabad, Telangana.
• Grade Level 11.