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:
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Mastery of application, data, infrastructure, and Agentic AI disciplines
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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
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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.
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Provide support to develop & improve the quality of technical engineering documentation
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Provide technical supervision, oversight and problem resolution for engineering activities
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Champion a DevOps model so that services are automated and elastic across all platforms
Required qualifications, capabilities, and skills:
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Google & Azure cloud expertise in a mission critical production environment
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Strong understanding about container technologies such as Docker, Kubernetes, GKE and HELM
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Experience in programming in one of the following languages: Python, shell scripting or GO along with good understanding of REST APIs
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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.
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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.
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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.
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Strong understanding about the Google Cloud governance and compliance and cost management
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Strong working knowledge of modern development technologies and tools such Agile, CI/CD, Git, Infrastructure as Code, Terraform and Jenkins.
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Google Cloud certification or equivalent technical experience in the Public Cloud.
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Good understanding of Agentic AI SDKs and GitHub Copilot Skills.
Preferred qualifications, capabilities, and skills:
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Good understanding of operating systems such as Windows, Linux (Redhat / Ubuntu)
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Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS