Principal Software Developer

AI-Driven Incident Remediation (LARS)

• Design and implement new LARS remediation workflows across single-tenant (ST) and multi-tenant (MT) OAC instances.
• Expand automated coverage for service health, capacity, cluster availability, and network-related alarms.
• Enhance AI-driven diagnostics, triage, pattern detection, and auto-approval pipelines for incident mitigation.
• Improve observability, cross-pod dashboarding, and multi-pod coordinated incident support.

• Develop and integrate AI-assisted diagnostics and automated mitigation for high-severity production incidents.
• Contribute to Agentic Dev Ops initiatives, including autonomous remediation frameworks and prototype agent workflows.
• Collaborate with ML teams to incorporate models for anomaly detection, root-cause analysis, and remediation recommendations.

• Build tooling and CI/CD pipeline extensions to eliminate manual change processes and streamline deployment safety.
• Design guardrails, approval workflows, and automated rollouts to improve release reliability and reduce operational toil.

• Develop MCP servers and agent orchestration workflows enabling end-to-end automated diagnostics and incident resolution.
• Integrate agent-driven actions with existing automation systems (LARS, CI/CD, service health signals).
• Contribute to next-generation self-healing and autonomous operations capabilities across OAC services.