Senior Lead Site Reliability Engineer

Lead Site Reliability Engineer

Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability. As a Lead Site Reliability Engineer at JPMorgan Chase within the Audit Technology, Production Management team, you hold a leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. Take lead and conduct resiliency design reviews, break up complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers.

Job Responsibilities

• Lead the Production Management team supporting Audit and Credit Review, setting direction, priorities, and performance expectations.

• Own stability, availability, resiliency, and end-to-end operational performance of business-critical Sales platforms, with clear accountability for outcomes.

• Act as a senior escalation point during critical incidents, driving rapid triage, decisive coordination, and recovery actions aligned to business impact.

• Drive operational consistency and service maturity through standardization, governance participation, service reviews, and disciplined support model integration for new capabilities.

• Lead reliability improvements by applying systems thinking and root-cause practices, expanding SRE adoption (observability, monitoring, automation, operational analytics), and improving supportability with engineering teams.

• Run strong incident, problem, and change management—major incident response, RCA and remediation to eliminate recurrence, and ensuring changes meet readiness standards (testing, monitoring, and resiliency/DR validation).

• 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.

• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls.

Required Qualifications, Capabilities, and Skills

• Formal training or certification on site reliability engineering concepts and 10+ years applied experience

• 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.

• Leadership experience across Production Support, Production Management, SRE, and Technology Operations teams, delivering stable and resilient production services.

• Strong systems thinking and problem-solving capability to assess complex, cross-domain production issues and drive end-to-end resolution.

• Demonstrated major incident leadership, coordinating effectively across teams to restore service rapidly and drive root-cause remediation.

• Track record of partnering with Application Development, Product, Sales, and business stakeholders to improve reliability, service quality, and operational maturity.

• Strong observability and service management expertise (Dynatrace, Splunk, Geneos, Grafana; ITIL Incident/Problem/Change/Availability), with excellent verbal/written communication and people leadership.

Preferred Qualifications, Capabilities, and Skills

• Demonstrated experience integrating support teams and standardizing operating models across multiple application groups to drive consistency and service maturity.

• Hands-on technology experience across cloud (AWS/Azure/GCP), automation and scripting (Python, Shell, PowerShell, Ansible, Terraform), and modern distributed platforms (containers, microservices, Kubernetes/OpenShift).