AI Product Manager
InstructureFull Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
The ideal candidate will bring deep expertise in AI/ML lifecycle management, enterprise observability, and automation, with a proven track record of building and leading high-performing teams in complex, large-scale environments. They will also partner closely with the AI Ops Architect to co-develop and execute a cohesive strategy that delivers measurable value across the organization, ensuring alignment between architectural vision and operational excellence.
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. 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 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. 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 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 solutions for performance and reliability optimization.
Develops and delivers prescription medicines globally
Eli Lilly and Company is a global pharmaceutical company that focuses on discovering, developing, and delivering medicines to improve health. The company has a long history of scientific achievements, including the creation of insulin, the first life-saving treatment for diabetes. Lilly's operations involve extensive research and development to create new medications and enhance existing ones, ensuring they are safe and effective. Their products are primarily prescription medicines sold to healthcare providers for various medical conditions, including diabetes, cancer, and pain management. What sets Lilly apart from its competitors is its strong commitment to ethical practices and the protection of its products from counterfeiting. The company's goal is to enhance lives through innovative medical solutions while maintaining high standards of quality and ethics.