Product Manager - Enterprise AI Operations & Observability

Job Summary

Product Manager - Enterprise AI Operations Observability

Hyderabad, India

Position Type: Full-Time

Level: P4

Position Summary

Eli Lilly is seeking a highly accomplished and hands on technology lead to drive our Enterprise AI Observability platform fuelling our ARE journey. This pivotal role is responsible for defining, implementing, and optimizing observability platform/s, and processes that ensure the reliability, performance, scalability, and security. The ideal candidate will bring deep expertise in driving of system of events end to end lifecycle management, self-serve instrumentation using agentic and automation, with a proven track in complex, large-scale environments. They will also partner closely with the ARE Architects and other platform engineers to execute a cohesive strategy that delivers measurable value across the organization, ensuring alignment between architectural vision and operational excellence.

Key Responsibilities

• Strategic Leadership Governance: Execute and drive forward a comprehensive strategy for enterprise observability.
• Strategic Leadership Governance: Establish governance frameworks, standards, and best practices for deployments.
• Strategic Leadership Governance: Ensure compliance with regulatory, security, and operational requirements.
• AIOps: Drive the adoption of AIOps practices for proactive issue detection, intelligent alerting, root cause analysis, and automated remediation.
• AIOps: Establish and scale practices for secure, efficient, and reliable deployment, observability, and lifecycle management of platform.
• Enterprise Observability: Enhance and maintain a robust observability strategy across infrastructure, applications, networks, security, and data systems.
• Enterprise Observability: Standardize the collection, correlation, and analysis of metrics, logs, and traces across all technology layers.
• Enterprise Observability: Build predictive capabilities and dashboards to anticipate failures and enable proactive interventions.
• Enterprise Observability: Treat observability as a product, continuously iterating to meet evolving business needs.
• Tooling, Platform Management Automation: Evaluate, implement, and manage advanced observability, and AIOps platforms and tools.
• Tooling, Platform Management Automation: Optimize and scale observability of infrastructure for high availability and performance.
• Tooling, Platform Management Automation: Design intuitive, high-value dashboards and alerting systems that clearly visualize system health and performance.
• Tooling, Platform Management Automation: Champion automation using scripting, orchestration tools, and AI-driven solutions to reduce manual effort and enable self-healing systems.
• Tooling, Platform Management Automation: Partner with automation teams to develop and implement automation scripts and workflows.
• Operational Resilience: Ensure high availability and resilience of mission-critical systems, especially AI/ML workloads.
• Operational Resilience: Collaborate closely with the Service Management Office and production support teams to drive impactful outcomes and elevate operational success
• Operational Resilience: Enable methods to reduce mean time recovery (MTTR) and drive continuous operational improvements.
• Performance Reliability Optimization: Utilize observability data to identify performance bottlenecks, capacity issues, and reliability risks.
• Performance Reliability Optimization: Work with relevant teams to implement improvements based on data-driven insights.
• Performance Reliability Optimization: Establish and execute performance strategy benchmarks utilizing baselines and KPIs.
• Team Leadership Enablement: Build, mentor, and lead a high-performing team of engineers and specialists in AIOps.
• Team Leadership Enablement: Provide training and documentation to operational teams on leveraging observability platforms for troubleshooting and performance tuning.
• Team Leadership Enablement: Foster a culture of innovation, continuous learning, and operational excellence.
• Cross-Functional Collaboration: Collaborate with engineering, data science, infrastructure, cybersecurity, and business teams to operationalize AI initiatives and ensure comprehensive observability coverage.
• Cross-Functional Collaboration: Serve as a subject matter expert to understand and deliver tailored observability solutions across teams.
• Budget Vendor Management: Manage departm…