Lead SRE- Azure & GCP

We have a Lead Site Reliability Engineer (SRE) opportunity within our Google Cloud Site Reliability Engineering team.

As a Lead Site Reliability Engineer at JPMorgan Chase within the Infrastructure Platform - Cloud Foundational Services SRE organization you will join our Google Cloud Site Reliability Engineering team operating within a global follow-the-sun support model.

Job Responsibilities:

• Lead and Implement SRE frameworks to support global google cloud environments and ensure the highest level of SLOs through operational excellence
• Mastery of application data infrastructure and Agentic AI disciplines
• Keen understanding of financial control and budget management using expertise in working in partnership with colleagues throughout the firm and in leading collaborative teams to achieve common goals
• Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage troubleshooting and post-incident analysis validating outputs and handling operational data according to sensitivity and security requirements.
• Provide support to develop & improve the quality of technical engineering documentation
• Provide technical supervision oversight and problem resolution for engineering activities
• Champion a DevOps model so that services are automated and elastic across all platforms

Required qualifications capabilities and skills:

• Google & Azure cloud expertise in a mission critical production environment
• Strong understanding about container technologies such as Docker Kubernetes GKE and HELM
• Experiencein programming in one of the following languages: Python shell scripting or GO along with good understanding of REST APIs
• Hands-on experience with cloud-based technologies and tools especially in deployment monitoring and operations such as Google Observability Azure Monitor Data Dog Prometheus Splunk Elasticsearch and Grafana.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g. incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity.
• Ability to evaluate AI-assisted operational recommendations for correctness and risk define appropriate guardrails for team usage and ensure outcomes align to resiliency and security expectations.
• Strong understanding about the Google Cloud governance and compliance and cost management
• Strong working knowledge of modern development technologies and tools such Agile CI/CD Git Infrastructure as Code Terraform and Jenkins.
• Google Cloud certification or equivalent technical experience in the Public Cloud.
• Good understanding of Agentic AI SDKs and GitHub Copilot Skills.

Preferred qualifications capabilities and skills:

• Good understanding of operating systems such as Windows Linux (Redhat / Ubuntu)
• Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS