You will be taken to JPMorgan Chase’s own careers page to apply. Job ID 210796575.
Job description
As a Senior Lead Site Reliability Engineer at JPMorgan Chase within the Reliability Engineering & Problem Management team, you will serve as the technical authority for post-incident investigations and operational resilience. You will lead deep technical reviews, validate causal analysis, and ensure corrective actions address systemic causes. You will partner with cross-functional teams to drive measurable improvements in reliability, resilience, and operational excellence. You will help ensure incidents translate into lasting engineering improvements and reduction of repeat failures. Job responsibilities
Serve as the technical authority for Problem Management-led Root Cause Analysis reviews across major incidents and service-impacting events
Lead deep-dive RCA challenge sessions, validating technical findings and causal chains through evidence-based analysis. Assess the quality and accuracy of root cause investigations, ensuring conclusions are technically sound and defensible. Challenge assumptions, unsupported conclusions, symptom-based findings, and ineffective corrective actions. Drive a culture of accountability focused on systemic learning and long-term reliability improvements
Evaluate detection gaps, monitoring effectiveness, observability shortcomings, automation opportunities, resilience weaknesses, process breakdowns, and human factors. Validate that corrective actions address the true root cause and reduce recurrence likelihood and impact. Review corrective actions for closure and effectiveness, ensuring intended reliability and operational outcomes. Provide technical challenge and independent review of vendor, third-party, and internal investigation reports
Use enterprise-authorized AI capabilities to accelerate reliability design and operational decisioning, validating outputs and handling operational data according to sensitivity and security requirements
Lead reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices, ensuring traceability, auditability, resiliency, and security controls. Define and govern Service Level Objectives, Service Level Indicators, Reliability Metrics, and Error Budgets
Evaluate system architecture against reliability design principles
Recommend resilience patterns including graceful degradation, dependency isolation, rate limiting, circuit breakers, fault tolerance, capacity management, auto-remediation, and self-healing capabilities
Lead reliability maturity assessments across platforms and services
Lead enterprise-authorized AI capabilities for RCA generation, incident analysis, log analytics, pattern discovery, problem trend analysis, and corrective action recommendations
Establish governance for explainability, auditability, data handling, and validation of AI-generated findings
Drive AI-assisted reliability workflows across the incident lifecycle
Required qualifications, capabilities and skills
Formal training or certification on security engineering concepts and 5+ years applied experience. Hands on experience in Infrastructure Engineering, Site Reliability Engineering, Production Engineering, Systems Engineering, or Software Engineering. Strong exposure to leading or supporting critical incident investigations
Experience conducting deep technical RCAs for enterprise-scale environments, working in highly regulated and mission-critical environments
Strong hands-on expertise in SLO/SLI Engineering, Distributed Tracing, Telemetry Design, Reliability Metrics, Error Budget Management, and AIOps Platforms
Experience with tools such as Splunk, Dynatrace, Grafana, Datadog, Prometheus, AppDynamics, Elastic, and Open Telemetry
Deep understanding of Root Cause Analysis methodologies, Five Whys, Fault Tree Analysis, Event Correlation, Human Factors Analysis, Systemic Cause Analysis, Problem Management Governance, and Major Incident Management
Demonstrated experience using enterprise-authorized AI capabilities to improve reliability engineering workflows with strong validation habits and awareness of data sensitivity
Ability to set team practices for safe AI usage in operations while maintaining resiliency, security, and auditability outcomes
Strong executive communication skills. Ability to challenge senior engineering stakeholders constructively. Proven ability to influence without direct authority
Ability to translate technical findings into executive-ready narratives
Preferred qualifications, capabilities and skills
Experience leading reliability engineering initiatives in large-scale, complex environments
Expertise in AI-enabled incident analysis and reliability workflows
Experience establishing governance for explainability and auditability of AI-generated findings
Demonstrated ability to drive measurable improvements in reliability, resilience, and operational excellence
