Senior Lead Site Reliability Engineer

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Commercial & Investment Bank

This role is for a Principal Site Reliability Engineer within JPMorgan Chase's Commercial & Investment Bank, Payments Technology team. The engineer will define non-functional requirements and availability targets, ensure NFRs are accounted for in design and testing, and implement service level objectives. A key aspect of the role involves using and leading the adoption of enterprise-authorized AI capabilities to enhance reliability design, operational decisioning, and workflows across the SDLC, while ensuring security, traceability, and auditability.

What you'd actually do

  1. Uses enterprise-authorized AI capabilities within the work environment to accelerate reliability design and operational decisioning (e.g., incident/post-incident analysis and requirements traceability), validating outputs and handling operational data according to sensitivity and security requirements.
  2. Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., testing/validation automation and production readiness), ensuring traceability/auditability, resiliency, and security controls.
  3. Collaborates with others to create and implement observability and reliability designs for complex systems that are robust, stable, and do not incur additional toil or technical debt.
  4. Provides advice and mentoring to other engineers and acts as a key resource for technologists seeking advice on technical and business-related issues
  5. Creates high quality designs, roadmaps, and program charters that are delivered by you or the engineers under your guidance

Skills

Required

  • Formal training or certification on site reliability engineering concepts and 5+ years applied experience
  • Advanced knowledge in site reliability culture and principles with demonstrated ability to implement site reliability within an application or platform
  • Advanced knowledge and experience in observability such as white and black box monitoring, service level objectives, alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment 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 (e.g., review/approval expectations and escalation paths) while maintaining resiliency, security, and auditability outcomes.
  • Advanced knowledge of software applications and technical processes with considerable depth in one or more technical disciplines
  • Ability to communicate data-based solutions with complex reporting and visualization methods
  • Recognized as an active contributor of the engineering community

Nice to have

  • Continues to expand network and leads evaluation sessions with vendors to see how offerings can fit into the firm’s strategy
  • Ability to anticipate, identify, and troubleshoot defects found during testing
  • Strong communication skills with ability to mentor and educate others on site reliability principles and practices

What the JD emphasized

  • Uses enterprise-authorized AI capabilities within the work environment to accelerate reliability design and operational decisioning
  • Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve reliability engineering workflows
  • Ability to set team practices for safe AI usage in operations