Product Manager – Enterprise AI Operations & Observability

Overview

Lead the Enterprise AI Observability platform that supports Eli Lilly's ARE journey, defining and optimizing observability platforms and processes for reliability, performance, scalability and security.

What you'll do

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

What you'll need

• Bachelor's or master's degree in computer science, engineering, IT, or a related field.
• 15+ years of progressive technology experience, including 5–7 years in enterprise operations, ARE/SRE and AI operations.
• Deep understanding of the lifecycle, including development, deployment, observability, and retraining.
• Proven experience with enterprise observability across hybrid environments.
• Expertise in AIOps principles and implementation.
• Proficiency with leading observability and MLOps tools and platforms.
• Strong knowledge of cloud platforms, containerization, and microservices.
• Excellent leadership, communication, and stakeholder management skills.
• Demonstrated ability to build and lead high-performing engineering teams.
• Strong analytical and data-driven decision-making skills.
• Tools: OpenTelemetry, Splunk, Datadog, Dynatrace, Prometheus, Grafana (PLGJ stack); Kubernetes, AWS, Azure, VMware, OpenShift; ServiceNow; MCP, REST APIs; Ansible, Terraform, Python, GitHub; Jira.

Nice to have

• Experience in regulated industries (e.g., healthcare, finance).
• Certifications in cloud platforms or operational frameworks (e.g., ITIL).
• Active participation in AIOps or MLOps professional communities.

Details

• Full-time, P4 level.
• Location: Hyderabad, India.
• Department: Tech@Lilly.