Product Manager – Enterprise AI Operations & Observability

Key Responsibilities

Strategic Leadership & Governance

· 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.

AIOps

· 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 platform.

Enterprise Observability

· 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.

Tooling, Platform Management & Automation

· 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.

Operational Resilience

· 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 recovery (MTTR) and drive continuous operational improvements.

Performance & Reliability Optimization

· 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.

Team Leadership & Enablement

· 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.

Cross-Functional Collaboration

· 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.

Budget & Vendor Management

· Manage departmental budgets and vendor relationships to deliver cost-effective, scalable solutions.

Qualifications

Required

· 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.

Monitoring & Observability Open Telemetry, Splunk, Datadog, Dynatrace, Prometheus, Grafana - PLGJ stack

Infrastructure Kubernetes, AWS, Azure, VMware, OpenShift

Data & Knowledge ServiceNow

Agentic & AI MCP, REST APIs

Automation & Runbooks Ansible, Terraform, Python, GitHub

Governance Jira

Preferred

· 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.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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