Hybrid Lead Observability Engineer

at Kobie

• Job title: Lead Observability Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Cloud, Distributed Systems, Kafka, Kubernetes, Splunk
• Location requirements: Hybrid, Bengaluru, India

About the role

• Lead Observability Engineer shaping observability practices within Kobie's new Tech Hub in India. Collaborate on global projects while enhancing system reliability and performance visibility.

Responsibilities

• Own and evolve the observability platform (e.g., New Relic) to provide end-to-end visibility across applications and infrastructure
• Establish standards for monitoring, alerting, dashboards, and telemetry (logs, metrics, traces)
• Leverage AIOps capabilities to improve anomaly detection, reduce noise, and accelerate root cause analysis
• Drive automation and self-healing workflows to minimize manual intervention and improve system resilience
• Collaborate across teams to ensure systems are observable by design and aligned with reliability goals
• Continuously analyze system behavior and incident patterns to improve performance, scalability, and uptime

Requirements

• 8–10+ years of experience in observability, site reliability engineering (SRE), DevOps, or advanced production operations in large-scale enterprise environments.
• Expert-level hands-on experience implementing and optimizing observability platforms such as New Relic, Datadog, Dynatrace, or Splunk.
• Strong understanding of monitoring fundamentals including logs, metrics, traces, and alerting strategies.
• Experience working with cloud-native architectures (AWS preferred).
• Familiarity with containerized environments and orchestration platforms such as Kubernetes.
• Experience integrating observability practices into CI/CD pipelines to ensure applications are observable by design.
• Strong understanding of incident management, problem management, and change management practices (ITIL concepts).
• Demonstrated ability to analyze telemetry data to identify patterns, detect anomalies, and improve operational reliability.
• Strong leadership and collaboration skills with the ability to coordinate across engineering, DevOps, and operations teams.
• Excellent communication skills and a strong focus on operational excellence and continuous improvement.
• Nice to Have: Experience implementing AI/ML capabilities within observability tools for anomaly detection and predictive monitoring.
• Familiarity with AIOps platforms and automated remediation workflows.
• Experience with event streaming platforms such as Kafka for telemetry ingestion or real-time data processing.
• Basic understanding of application architecture and troubleshooting distributed systems.
• Experience with automation frameworks or serverless workflows (e.g., AWS Lambda, scripting, or infrastructure automation).

Benefits

• Comprehensive health coverage
• Well-being perks
• Flexible time off
• Public holidays recognition