Senior Lead Site Reliability Engineer-network Etrade Infra

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Corporate Sector

This role focuses on infrastructure engineering, specifically in networking for electronic trading services. While it involves using enterprise-authorized AI capabilities to enhance reliability design, operational decisioning, and SDLC workflows, the core function is not building AI models but rather leveraging existing AI tools to improve infrastructure operations. The role requires expertise in networking, cloud infrastructure, and setting practices for safe AI usage in operations.

What you'd actually do

  1. Apply technical expertise and problem-solving methodologies to projects of moderate scope
  2. Drive workstreams or projects involving one or more infrastructure engineering technologies
  3. Collaborate with other platforms to architect and implement changes that resolve issues and modernize technology processes
  4. 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.
  5. 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.

Skills

Required

  • Formal training or certification in networking concepts and demonstrate advanced proficiency
  • Deep knowledge in one or more areas of infrastructure engineering, such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
  • 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.
  • Commitment to developing technical and cross-functional knowledge beyond your product area
  • Deep knowledge of cloud infrastructure and multiple cloud technologies, with the ability to operate in and migrate across public and private clouds

Nice to have

  • Experience with Arista, Cisco, F5, and Fortinet devices
  • Familiarity with network automation tools and techniques, such as Ansible
  • Experience with Corvil and Wireshark

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