- Location
- India GCC-Puppalaguda Village
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Closing date
- Today
- Source
- Workday
Description
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Role Overview
We are seeking a Senior Delivery Lead – AIOps to serve as the execution “quarterback” across AIOps initiatives and Security programs. This role focuses on ensuring that emerging ideas—from enterprise AIOps efforts—are consistently translated into production-grade solutions that are operationalized and adopted.
You will drive alignment, execution discipline, and follow-through across multiple teams, ensuring that AI-enabled capabilities deliver measurable outcomes in operational reliability, efficiency, and resiliency.
Key Responsibilities
- Act as the single delivery owner for AI enablement across major CTO programs, ensuring cohesion and momentum across parallel efforts.
- Orchestrate AI-centric delivery using consistent patterns, tooling, and governance to drive repeatable, production-grade execution.
- Translate AIOps capabilities into deployed, operational outcomes—ensuring solutions are embedded into day-to-day operations and adopted.
- Drive cross-functional execution across CTO teams including Infrastructure, Platform, Data, Automation/AI enablement, and Cybersecurity & Security initiatives.
- Establish execution discipline for AI initiatives, including milestones, dependency management, risk, and value realization.
- Operationalize learnings from weekly AIOps sessions into prioritized, funded, and delivered initiatives that scale beyond pilots.
- Ensure AI solutions are production-ready, secure, compliant, and operationally supportable in a regulated, high-reliability environment.
- Identify and remove systemic delivery blockers related to data quality, integration, tooling, or operating model constraints; escalate early to protect outcomes.
How Success Will Be Measured
- Percentage of AI initiatives successfully deployed into production and adopted by operations.
- Time-to-value from AI initiative approval to measurable operational impact.
- Demonstrated improvement in execution cohesion across parallel AI initiatives.
- Reuse of standardized AI delivery patterns across CTO programs.
- Positive risk, audit, and compliance outcomes for AI-enabled capabilities.
Required Qualifications
- Proven experience driving complex, cross-functional delivery in large enterprise environments.
- Practical experience applying AI/AIOps in production environments.
- Strong outcome-first mindset and execution discipline.
- Strong systems thinking and understanding of enterprise technology operations.
- Experience managing dependencies, risks, and stakeholder alignment.
- Comfortable operating in regulated, high-reliability environments.
Preferred / Nice to Have
- Experience partnering across Infrastructure, Platform, Data, and Cybersecurity teams.
- Experience implementing consistent delivery patterns and governance.
- Exposure to IT operations, resiliency, automation, or ITSM modernization.