Lead SRE - AWS Platform
Job in
Glasgow, Glasgow City Area, G1, Scotland, UK
Listed on 2026-08-23
Listing for:
JPMorgan Chase & Co.
Full Time
position Listed on 2026-08-23
Job specializations:
-
IT/Tech
SRE/Site Reliability, Cloud Computing: Infrastructure & Operations, Systems Engineer
Job Description & How to Apply Below
Assume a critical role in defining the future of a globally recognized firm and make a direct, meaningful impact in a space built for top achievers in site reliability engineering.
As a Lead Site Reliability Engineer at JPMorgan
Chase within Infrastructure Platforms, you bring deep technical expertise across multiple domains and play a key role in driving reliability outcomes for your team. You will conduct resiliency design reviews, break complex problems into digestible work, act as a technical authority for medium to large-sized products, and share your knowledge and experience with peers to raise the bar across the team.
- Consistently champion site reliability culture and practices, documenting and sharing knowledge across your organization through internal forums and communities of practice
- Drive initiatives to improve the reliability and stability of your team's applications and platforms using data-driven analytics to improve service levels, proactively identifying and resolving technology-related bottlenecks
- Collaborate with your team to identify comprehensive service level indicators and partner with stakeholders to establish reasonable service level objectives and error budgets
- Design and implement observability frameworks and alerting strategies, including white and black box monitoring, service level objective-based alerting, and telemetry collection to ensure proactive detection and response
- Serve as the primary point of contact during major incidents for your application, applying strong diagnostic skills to identify and resolve issues quickly and minimize business impact
- Apply deep technical expertise within one or more technical domains, sharing knowledge and providing guidance to peers across the team
- Drive reuse-first adoption of AI-assisted reliability workflows across the software development lifecycle and toolchain practices (e.g., continuous integration/continuous delivery quality checks, test and validation automation, and operational readiness), ensuring traceability, auditability, resiliency, and security controls
- Use 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
- Formal training or certification on site reliability engineering concepts and advanced applied experience
- Demonstrated hands-on experience with Amazon Web Services (AWS), including deploying, operating, and maintaining resilient, highly available workloads in a cloud environment
- Demonstrated proficiency in reliability, scalability, performance, and enterprise system architecture, with hands-on experience conducting resiliency design reviews and implementing resiliency best practices
- Fluency in at least one programming language such as Python, Java/Spring Boot, or .NET
- Proficient knowledge and experience in observability, including white and black box monitoring, service level objective alerting, and telemetry collection across large-scale production environments
- Proficiency with continuous integration and continuous delivery practices and tooling
- Proficiency with container technologies and container orchestration
- Experience troubleshooting common networking technologies and issues
- Advanced knowledge of software applications and technical processes with emerging depth in one or more technical disciplines, with a demonstrated ability to evaluate and recommend suitable new technologies
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve site reliability engineering 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
- Experience with cloud platforms and infrastructure-as-code tooling in an enterprise environment
- Familiarity with chaos engineering principles and proactive resiliency testing practices
- Experience contributing to communities of practice, internal knowledge-sharing forums, or engineering guilds
- Exposure to advanced observability platforms and distributed tracing in large-scale production environments
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