Product Manager Enterprise AI Operations & Observability

As a Product Manager for Enterprise AI Operations & Observability at Lilly, you will play a crucial role in defining, implementing, and optimizing operational frameworks to ensure the reliability, performance, scalability, and security of AI/ML systems and the broader enterprise technology landscape. Key Responsibilities: - Develop and execute a comprehensive strategy for enterprise AI operations and observability aligned with business and technology goals. - Establish governance frameworks, standards, and best practices for AI/ML deployments and enterprise observability. - Drive the adoption of AIOps practices for proactive issue detection, intelligent alerting, root cause analysis, and automated remediation. - Establish and scale MLOps practices for secure, efficient, and reliable deployment, observability, and lifecycle management of AI/ML models. - Define and implement a robust observability strategy across infrastructure, applications, networks, security, and data systems. - Evaluate, implement, and manage advanced observability, and AIOps platforms and tools. - Ensure high availability and resilience of mission-critical systems, especially AI/ML workloads. - Utilize observability data to identify performance bottlenecks, capacity issues, and reliability risks. - Build, mentor, and lead a high-performing team of engineers and specialists in AIOps. Qualifications Required: - Bachelor's or master's degree in computer science, Engineering, IT, or a related field. - 15+ years of progressive technology leadership experience, including 57 years in enterprise operations, SRE, or AI/ML operations. - Deep understanding of the AI/ML lifecycle, including development, deployment, observability, and retraining. - Proficiency with leading observability and MLOps tools and platforms. - Excellent leadership, communication, and stakeholder management skills. - Demonstrated ability to build and lead high-performing engineering teams. Preferred Qualifications: - 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. At Lilly, we are dedicated to providing equal opportunities for all individuals, including those with disabilities. We do not discriminate based on age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability, or any other legally protected status. As a Product Manager for Enterprise AI Operations & Observability at Lilly, you will play a crucial role in defining, implementing, and optimizing operational frameworks to ensure the reliability, performance, scalability, and security of AI/ML systems and the broader enterprise technology landscape. Key Responsibilities: - Develop and execute a comprehensive strategy for enterprise AI operations and observability aligned with business and technology goals. - Establish governance frameworks, standards, and best practices for AI/ML deployments and enterprise observability. - Drive the adoption of AIOps practices for proactive issue detection, intelligent alerting, root cause analysis, and automated remediation. - Establish and scale MLOps practices for secure, efficient, and reliable deployment, observability, and lifecycle management of AI/ML models. - Define and implement a robust observability strategy across infrastructure, applications, networks, security, and data systems. - Evaluate, implement, and manage advanced observability, and AIOps platforms and tools. - Ensure high availability and resilience of mission-critical systems, especially AI/ML workloads. - Utilize observability data to identify performance bottlenecks, capacity issues, and reliability risks. - Build, mentor, and lead a high-performing team of engineers and specialists in AIOps. Qualifications Required: - Bachelor's or master's degree in computer science, Engineering, IT, or a related field. - 15+ years of progressive technology leadership experience, including 57 years in enterprise operations, SRE, or AI/ML operations. - Deep understanding of the AI/ML lifecycle, including development, deployment, observability, and retraining. - Proficiency with leading observability and MLOps tools and platforms. - Excellent leadership, communication, and stakeholder management skills. - Demonstrated ability to build and lead high-performing engineering teams. Preferred Qualifications: - 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. At Lilly, we are dedicated to providing equal opportunities for all individuals, including those with disabilities. We do not discriminate based on age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran s