We are seeking a highly skilled DevOps Solution Architect to lead the design, automation, deployment, and operational excellence of modern enterprise platforms and software solutions. This role bridges software architecture, cloud infrastructure, DevOps engineering, and AI-enabled and human in the loop operational practices to ensure scalable, secure, and resilient delivery pipelines and production environments.

The ideal candidate combines deep technical expertise and operational experience with mission critical, high availability applications. The candidate must embrace an AI-first mindset — leveraging AI-assisted development, automation, monitoring, troubleshooting, and optimization practices throughout the software delivery lifecycle.

You will work closely with engineering, infrastructure, security, QA, and business stakeholders to architect and implement modern DevOps solutions that accelerate software delivery while improving reliability, observability, and operational efficiency. You will also proactively monitor the platform, triage application and system alerts, and coordinate incident response to ensure the stability and availability of critical services.

Responsibilities:

• Design, develop, and maintain scalable, secure, and highly available cloud-native and hybrid infrastructure and DevOps architectures.
• Actively monitor the platform across environments and respond to any alerts using automation or manual procedures.
• Develop SOPs to handle common alerting scenarios in Production for other support teams to use after hours.
• Implement and evolve enterprise DevOps standards, CI/CD pipelines, Infrastructure-as-Code (IaC), automation frameworks, and operational best practices.
• Design and implement enterprise monitoring, logging, alerting, observability, and AI-enhanced operational intelligence solutions across infrastructure and applications.
• Establish operational health metrics, SLIs/SLOs, dashboards, and proactive monitoring strategies to ensure production reliability, performance, scalability, and rapid incident response.
• Collaborate with software development teams to align application architecture, deployment processes, infrastructure, security, and operational requirements throughout the software delivery lifecycle.
• Promote an AI-first engineering culture by leveraging AI-assisted automation, monitoring, diagnostics, security analysis, troubleshooting, and operational optimization capabilities.
• Ensure production readiness through resiliency testing, disaster recovery planning, security compliance, vulnerability management, secrets management, and operational automation.
• Drive continuous improvement initiatives through rapid prototyping, evaluation of emerging technologies, root cause analysis, and implementation of AI-powered solutions that improve platform reliability, deployment efficiency, and developer productivity.