Lead SRE- Azure & GCP

JPMorgan Chase & Co.; Glasgow; On-site; GBP 90,000 - 150,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Site Reliability Engineer to drive SRE excellence for Google Cloud environments. You will lead global frameworks, champion a DevOps culture, and oversee incident response and documentation across the infrastructure platforms team.

The role requires cloud proficiency (Google Cloud, Azure), container tech (Docker, Kubernetes, GKE, Helm), and strong scripting with Python/Go. Expect collaboration with cross-functional teams and governance-aware operations.

Qualifications

• Experience with Google Cloud and Azure in production environments.
• Strong container technology knowledge: Docker, Kubernetes, GKE, HELM.
• Proficient in programming: Python, Shell, or Go with REST APIs.
• Hands-on with cloud tools for deployment, monitoring and operations (e.g., Google Observability, DataDog, Prometheus, Grafana).
• Experience applying enterprise AI capabilities to improve SRE workflows with validation and data sensitivity awareness.
• Ability to evaluate AI-driven recommendations, set guardrails, and align outcomes with resiliency and security.

Responsibilities

• Lead and implement SRE frameworks to support global Google Cloud environments and ensure high SLOs.
• Leverage AI to accelerate incident triage, troubleshooting and post-incident analysis.
• Collaborate across teams on budgets and cost management in a large firm.
• Develop and improve technical engineering documentation.
• Provide supervision and oversight for engineering activities.
• Promote a DevOps model so services are automated and elastic across platforms.

Skills

Google Cloud

Azure Cloud

SRE frameworks

SLOs management

DevOps practice

AI in operations

Incident response

Governance & compliance

AI guardrails

Security awareness

Tools

Docker

Kubernetes

GKE

HELM

Prometheus

Grafana

DataDog

Splunk

Elasticsearch

Terraform

Jenkins

Git

CI/CD

Job description

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