SRE Software Engineer III

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 120,000 - 190,000; Full time

Job summary

JPMorganChase is seeking an SRE Software Engineer III within Corporate Technology to design, build, and operate resilient software that improves availability, scalability, and customer experience.

You will collaborate across engineering and stakeholder groups to implement automated delivery, observability, and secure coding practices, while reducing toil and strengthening reliability at scale.

Qualifications

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Proficiency in site reliability culture and principles within an application or platform.
• Proficiency in Python, Java/Spring Boot, or .NET.
• Experience building observability solutions with telemetry and SLO-based alerting using Grafana, Dynatrace, Prometheus, Datadog, or Splunk.
• Experience with CI/CD tools such as Jenkins, GitLab, or Terraform.
• Familiarity with containers and orchestration such as Docker, Kubernetes, or AWS ECS.
• Knowledge of distributed systems networking and troubleshooting.
• Ability to adopt new technologies and improve delivery outcomes with AI-assisted tooling, with focus on safety and security.

Responsibilities

• Design and implement automated CI/CD pipelines to improve release quality, speed, and repeatability.
• Develop, test, and deliver software enhancing availability, reliability, and operational readiness.
• Collaborate with engineers and stakeholders to troubleshoot multi-system problems and restore services.
• Define and monitor service level indicators and objectives to reduce customer impact.
• Advance observability with telemetry, dashboards, and alerting to shorten mean time to detect and recover.
• Improve operational excellence via runbooks, automation, and continuous improvement actions.
• Leverage enterprise AI coding assist tools to improve code quality and productivity; ensure outputs are validated for correctness and security.
• Apply SDLC tooling knowledge, including AI-assisted development and automation, to maximize value of automation.

Skills

Site reliability principles

Programming in Python/Java/.NET

Observability and monitoring

CI/CD concepts

Networking in distributed systems

Tools

Jenkins

GitLab

Terraform

Docker

Kubernetes

Grafana

Dynatrace

Prometheus

Datadog

Splunk

Job description

Build technology that powers critical business outcomes at JPMorganChase. Join a collaborative engineering team where you can grow your skills, strengthen reliability at scale, and help deliver resilient customer experiences.

As an SRE Software Engineer III at JPMorganChase within Corporate Technology, you will build and operate resilient software solutions that improve availability, scalability, and customer experience. You will collaborate across engineering and stakeholder groups to design automated delivery approaches, apply site reliability principles, and resolve complex issues before they impact users.

Job Responsibilities

• Design and implement automated continuous integration and continuous delivery pipelines to improve release quality, speed, and repeatability
• Develop, test, and deliver software solutions that strengthen availability, reliability, scalability, and operational readiness of applications and services
• Partner with engineers, technical experts, and key stakeholders to troubleshoot and resolve complex, multi-system problems to restore service and prevent recurrence
• Define and use service level indicators and service level objectives to proactively identify risk, prioritize reliability improvements, and reduce customer impact
• Advance observability practices by improving telemetry, dashboards, and alerting to shorten time-to-detect and time-to-recover
• Improve operational excellence through runbooks, automation, and continuous improvement actions that reduce toil and production risk
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Proficiency in site reliability culture and principles, including applying reliability practices within an application or platform
• Proficiency in at least one programming language such as Python, Java/Spring Boot, or .NET
• Experience building observability solutions, including telemetry collection and service level objective-based alerting using tools such as Grafana, Dynatrace, Prometheus, Datadog, or Splunk
• Experience with continuous integration and continuous delivery tools such as Jenkins, GitLab, or Terraform
• Familiarity with containers and orchestration technologies such as Docker, Kubernetes, or Amazon Elastic Container Service
• Working knowledge of diagnosing and troubleshooting common networking concepts and issues in distributed systems
• Ability to proactively remove blockers, learn new technologies, and apply new approaches to improve delivery outcomes
• Working knowledge of using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred Qualifications, Capabilities, and Skills

• Experience designing reliability improvements using error budgets, capacity planning, and resilience patterns (e.g., rate limiting, backpressure, graceful degradation)
• Experience improving release safety with progressive delivery practices (e.g., canary deployments, feature flags, automated rollbacks)
• Experience implementing automated quality gates (unit, integration, performance, and security testing) within delivery pipelines
• Exposure to incident management practices, post-incident reviews, and implementing measurable remediation actions to prevent recurrence
• Familiarity with infrastructure-as-code and standardized environment provisioning to improve consistency and auditability