About the role
AI Engineer AI/ML with AIOps
AIOps : Technical Lead - Offshore
5+ Yrs
Bengalore
Role Summary:
As the Monitoring, AIOps, and Observability Technology Lead, you will be responsible for defining and executing the strategy, architecture, and implementation of enterprise-grade observability and monitoring solutions. This role is pivotal in ensuring system reliability, performance, and proactive incident management across complex, distributed, and cloud-native environments.
Key Responsibilities:
• Define and evolve the observability and AIOps strategy aligned with business KPIs and SLAs.
• Lead the design and implementation of scalable monitoring and observability platforms.
• Drive the adoption of AIOps capabilities for predictive analytics, anomaly detection, and automated incident response.
• Oversee the end-to-end observability stack including metrics, logs, traces, and events.
• Manage tools such as Splunk, Dynatrace, Prometheus, Grafana, Open Telemetry, Datadog, Azure Monitor, AWS CloudWatch, and ServiceNow Event Management.
• Work with DevOps, SRE, Cloud, and Application teams to embed observability into CI/CD pipelines and system architectures.
• Define and enforce observability standards, best practices, and governance models.
• Develop and maintain dashboards, alerts, and SLO/SLI frameworks to monitor system health and performance.
• Continuously optimize monitoring configurations to reduce MTTR and improve system reliability.
• Mentor and lead a team of observability and monitoring engineers.
• Foster a culture of continuous improvement, innovation, and operational excellence.
Required Qualifications:
• 8+ years of experience in IT infrastructure, DevOps, or SRE roles with a strong focus on monitoring and observability.
• Proven experience with AIOps platforms and observability tools (e.g., Splunk, Dynatrace, Prometheus, Grafana, Open Telemetry).
• Deep understanding of cloud platforms (AWS, Azure, GCP) and cloud-native monitoring practices.
• Experience integrating observability with ITSM tools (e.g., ServiceNow).
• Excellent communication and stakeholder management skills.
Preferred Qualifications:
• Certifications in AWS, Azure, or GCP.
• Experience with machine learning-based monitoring and predictive analytics.
• Familiarity with microservices, Kubernetes, and containerized environments.
• Experience in Finance industries is a plus.