
at J.P. Morgan
Bulge Bracket Investment BanksPosted a month ago
No clicks
**Lead Site Reliability Engineer - Network** As a Senior Lead, guide JPMorgan Chase's Enterprise Infrastructure Platforms team in defining and enhancing network reliability. Champion site reliability culture and practices, driving data-driven improvements to service levels. Architect automated solutions using Python, Shell, and Ansible to reduce toil. Own reliability for mission-critical network services, leading major incident response and post-incident learning. Collaborate with platform teams to integrate SRE practices and adopt AI-assisted reliability workflows. Key Responsibilities: - Lead resiliency design reviews and mentorship - Break down complex problems and drive incident reduction - Provide technical guidance for medium to large scale products - Oversee reliability for mission-critical network services - Leverage AI capabilities for incident management and knowledge capture Required Skills & Experience: - 5+ years in Site Reliability Engineering - Proficient in Python, Java/Spring Boot, .Net, and AI-assisted tools - Strong network troubleshooting, observability, and CI/CD experience - Proven leadership, incident response, and collaboration skills
- Compensation
- Not specified
- City
- Not specified
- Country
- United States
Currency: Not specified
Full Job Description
Location: OH, United States
Job responsibilities
Consistently models and champions site reliability culture and practices, documents and shares knowledge within your organization via internal forums and communities of practice
Leads initiatives to improve the reliability and stability of your teams applications and platforms using data-driven analytics to improve service levels, proactively identifying and solving technology-related bottlenecks in areas of expertise
Drives collaboration with your team to identify comprehensive service level indicators and the stakeholder partners to establish reasonable service level objectives and error budgets with your customers
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.
Serves as the main point of contact during major incidents for your application and has the skills to identify and solve the issue quickly to avoid financial loss to the business
Offers a high level of technical expertise within one or more technical domains and provides advice and mentorship to other engineers
- Own reliability for mission-critical network services (availability, performance, recoverability), leading major incident response, and driving strong post-incident learning.
- Own problem management end-to-end: author/approve RCAs, identify systemic root causes, and deliver durable remediation that prevents repeat incidents.
- Architect and deliver automation using Python, Shell, and Ansible (self-healing where appropriate, automated remediation with guardrails, validation pipelines, and standardized tooling) to reduce toil and improve reliability.
- Provide deep technical leadership across SD-WAN/SDA/SDN, routing & switching, and network security/traffic services (firewalls, load balancers, proxies), partnering with platform teams on observability and embedding SRE practices (NFR targets, FMEA-style risk analysis, readiness reviews, resilience testing, and change safety).
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.
Formal training or certification on site reliability engineering concepts and 5+ years applied experience
Demonstrated proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices
Fluent in at least one programming language such as: Python, Java/Spring Boot, .Net
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.
Proficient knowledge and experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection
Proficient with continuous integration and continuous delivery practices and tooling
Proficient with container and container orchestration
Experience with troubleshooting common networking technologies and issues
Advanced knowledge of software applications and technical processes with emerging depth in one or more technical disciplines, and actively self-educates to evaluate and recommend suitable new technologies




