Lead SRE - AWS Platform

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

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 JPMorganChase 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.

Job responsibilities

• 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

Required qualifications, capabilities, and skills

• 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

Preferred qualifications, capabilities, and skills

• 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