Lead Platform Engineer DevOps​/AWS​/Kubernetes

Position: Lead Platform Engineer DevOps / AWS / Kubernetes
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan

Chase within the Consumer & Community Banking Platform Engineering team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

Leads the design, development, and evolution of a highly scalable and reliable GraphQL platform serving multiple teams and business units

Utilizes containerization and orchestration technologies such as Docker and Kubernetes to manage large-scale workloads Establishes and champions observability, monitoring, and alerting standards across the platform, designing proactive solutions to detect and resolve issues before they impact users

Leads the development of automation strategies for CI/CD pipelines and infrastructure-as-code practices, creating reusable patterns and frameworks that accelerate delivery across engineering teams   Designs and oversees intuitive self-service developer experiences, including APIs, tooling, documentation, and integration patterns that enable teams to adopt platform services independently   Contributes to open-source projects or technical communities related to GraphQL, platform engineering and AWS services   Scripts and automates using Python and utilizes  Terraform and infrastructure-as-code practices for managing complex, multi-environment infrastructure   Architects in GraphQL architecture, schema design, and RESTful API, with experience designing and implementing API standards   Utilizes workflows (Git/Bitbucket) and distributed systems monitoring using tools such as Splunk, Data Dog, Dynatrace, or Cloud Watch   Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team  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 5+ years applied experience  Proven leadership experience in mentoring engineers, leading technical initiatives, and driving architectural decisions across teams   Expert in containerization and orchestration technologies such as Docker and Kubernetes and expert-level proficiency in scripting and automation using Python or similar language (Bash, Groovy)   Deep hands-on experience with Terraform and infrastructure-as-code practices for managing complex, multi-environment infrastructure   Strong expertise in GraphQL architecture, schema design, and RESTful API principles, with experience designing and implementing API standards   Expert-level proficiency with version control workflows (Git/Bitbucket) and distributed systems monitoring using tools such as Splunk, Data Dog, Dynatrace, or Cloud Watch    Deep understanding of OAuth 2.0, secure authentication/authorization patterns, and security best practices in platform engineering

Extensive experience with AWS cloud…