At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
Product Manager – Enterprise AI Operations & ObservabilityDepartment: Tech@LillyLocation: Hyderabad, IndiaPosition Type: Full-TimeLevel: P4Position SummaryEli Lilly is seeking a highly accomplished and strategic technology leader to head our Enterprise AI Operations (AIOps) and Observability functions. This pivotal role is responsible for defining, implementing, and optimizing operational frameworks, platforms, and processes that ensure the reliability, performance, scalability, and security of AI/ML systems and the broader enterprise technology landscape. 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.Key ResponsibilitiesStrategic Leadership & Governance
- 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.
AIOps & MLOps Maturity
- 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.
Enterprise Observability
- 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.
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 AI/ML 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 leadership experience, including 5–7 years in enterprise operations, SRE, or AI/ML operations.
- Deep understanding of the AI/ML 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.
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.#WeAreLilly
