Hands-on Data & Al Solutions for Operations Support
• Actively lead and contribute to high-impact data/AI projects that directly improve operations support outcomes — e.g., real-time incident enrichment, predictive alerting, automated root-cause analysis, change risk scoring, ticket clustering & autotriage, knowledge mining for support agents, and intelligent runbooks.
• Design and deliver scalable features embedded into operations support workflows and platforms (ServiceNow, Jira Service Management, monitoring tools, ITSM systems, etc.) in collaboration with multidisciplinary competency teams.
• Ensure solutions meet strict operations support SLAs for reliability, low latency, auditability, explainability, and zero-downtime deployment.
• Up-to-date with innovations and research in AIOPS Tools
AIOps Tools & Platform Leadership for Operations Support
• Lead the architecture, development, and continuous enhancement of internal AIOps platforms and reusable components that power operations support teams — including integration with ITSM, observability (Prometheus/Grafana/ELK/Dynatrace/Splunk), ticketing, and automation tooling.
• Support MLOps/AlOps best practices specifically for production operations support Al systems: model monitoring in live ops environments, drift & performance degradation detection, rollback mechanisms, and cost control at operational scale.
Al Technical Leadership for Operations Support Initiatives
• Serve as the lead Al technical authority and trusted advisor for all operations support programs, automation movements, and Al transformation efforts across service operations, NOC, support desks, infrastructure operations, and reliability engineering.
• Lead technical discussions, architecture reviews, PoCs, vendor evaluations, and solution selection whenever Al is being considered or applied to operations support challenges.
• Identify, prioritize, and drive the highest-ROI Al use cases in operations support —
e.g., reducing MTTR/MTTD, automating Level 1 triage, predicting PI incidents, autogenerating post-mortems, optimizing shift handovers, and enabling proactive operations support.
• Build, mentor, and lead a high-performing squad of AIOps specialists focused on operations support outcomes.
• Foster a culture of rapid experimentation, production-first mindset, and relentless focus on operational impact (reduced toil, faster resolution, higher availability).
• Perform technical coaching, design/code reviews, and career development with emphasis on operations support domain knowledge.
Stakeholder & Cross-Functional Collaboration
• Partner intensively with operations support leaders, incident managers, service owners, reliability engineers, ITSM/process teams, and infrastructure groups to align Al initiatives with operational priorities and pain points.
• Strong collaboration with DS&AI Competency.