Lead Platform Engineer DevOps / AWS / Kubernetes
Lead Platform Engineer building and scaling a GraphQL platform on AWS and Kubernetes, automating CI/CD, and driving observability and developer experience for multiple teams.
- Compensation
- Not disclosed
- Location
- Columbus, OH, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Devops
- Posted
Skills
Full description
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 JPMorganChase 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, DataDog, Dynatrace, or CloudWatch
- 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.