ITOPS / Observability AI Architect

Key Responsibilities
Develop end-to-end observability and AIOps architectures for large-scale enterprise
environments.
Define standards and best practices for monitoring, alerting, and automated
remediation.
Drive the deployment and integration of observability platforms and AIOps tools
across hybrid and multi-cloud environments.
Ensure seamless integration with ITSM, DevOps, and CI/CD pipelines.
Evaluate emerging technologies in observability and AIOps to recommend strategic
adoption.
Design AI/ML-driven predictive analytics for proactive incident management and
root cause analysis.
Work closely with clients, operations, and business teams to align architecture with
organizational goals.
Mentor technical teams on observability and AIOps best practices.
Optimize system performance through advanced telemetry, distributed tracing, and
anomaly detection.
Implement automated workflows for incident prevention and resolution.

Experience Qualifications
MCA, B.E degree in Computer Science, or related field.
10+ years in IT architecture or technical leadership roles.
Proven expertise in observability tools (e.g., Dynatrace, Datadog, New Relic,
Prometheus, Grafana) and AIOps platforms (e.g., Moogsoft, BigPanda, ServiceNow
AIOps).
Strong experience with Azure/AWS cloud architectures, containerization (Docker),
and orchestration (Kubernetes).
Hands-on experience with automation frameworks and infrastructure-as-code
(Terraform, Ansible).
Hands-on experience in IT operations preferably with IT infrastructure and
applications services

Skills:
Deep understanding of monitoring, logging, distributed tracing, and telemetry.
Knowledge of AI/ML concepts applied to IT operations.
Excellent problem-solving, communication, and leadership skills
Good understanding and exposure to ITIL frameworks

Preferred:
Certifications in cloud platforms (AWS/Azure), Kubernetes, or observability tools.
Experience in designing self-healing systems and predictive analytics for IT
operations.