DevOps AWS Software Engineer III

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Consumer and community Banking,  you will help build, operate, and scale AWS-based production environments (with a focus on EKS/ECS), support secure edge delivery via Akamai, and enable the deployment and ongoing operation of AI enabled services/workflows. You will be a key contributor to reliability, observability, automation, and operational excellence.

Job Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Manage, scale, and troubleshoot AWS infrastructure, focusing on containerized workloads running on EKS and ECS. Provision and maintain infrastructure using Terraform to ensure repeatable, standards-based deployments across environments. Support and improve CI/CD pipelines for application and AI-enabled feature releases (deployment automation, rollback support, and environment promotion). Collaborate with engineering teams to implement operational best practices (health checks, readiness, scaling, and resiliency patterns).
• 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.
• Administer and optimize Akamai CDN configurations for performance, caching, and edge troubleshooting. Implement and maintain Akamai Client Side Protection (CSP) configurations and support web security controls to reduce client-side threats (e.g., XSS/data exfiltration). Support certificate lifecycle activities (CSR generation, SAN/hostname validation, chain deployment, renewal coordination) and schedule changes to minimize downtime. Follow secure operational practices around secrets handling, access controls, and vulnerability remediation coordination
• Build and maintain dashboards and alerts using tools such as Splunk and metrics-based monitoring to improve early detection and reduce false positives. Participate in incident response: triage, escalation, mitigation, stakeholder updates, and post-incident follow-ups. Contribute to root cause analysis (RCA) and implement preventative fixes to reduce recurrence. Create and maintain operational documentation (runbooks, SOPs, on-call playbooks).

• Support change management: peer reviews, risk awareness, pre/post checks, and safe execution during maintenance windows. Working knowledge of incident and change management practices (ITSM mindset, clear comms, disciplined execution).

  Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Hands-on experience with AWS and container platforms (EKS and/or ECS).

• Experience using Terraform (or comparable IaC) for provisioning and managing infrastructure.

  Strong troubleshooting skills across Linux, networking fundamentals, and application/runtime behaviors.

  Working knowledge of incident and change management practices (ITSM mindset, clear comms, disciplined execution).

  Scripting/automation experience (e.g., Bash, Python, Perl) and CI/CD tooling exposure.

• Hands-on experience 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.
• Solid understanding of agile methodologies such as CI/CD, Application Resilienc…