Lead Devops Engineer- Aws/kubernetes

JPMorgan Chase JPMorgan Chase · Banking · Columbus, OH +1 · Consumer & Community Banking

Lead DevOps Engineer with a focus on AWS and Kubernetes, responsible for building and scaling platform solutions and infrastructure. The role involves executing software solutions, developing secure production code, and leveraging enterprise-authorized AI coding assist tools to improve code quality and productivity. The engineer will also lead communities of practice, drive automation strategies for CI/CD pipelines, and establish observability standards.

What you'd actually do

  1. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  2. Develops secure high-quality production code, and reviews and debugs code written by others
  3. 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.
  4. 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.
  5. Leads the design, development, and evolution of a highly scalable, reliable GraphQL platform with exceptional performance and high availability across multiple teams and services.

Skills

Required

  • 6+ years of professional software engineering experience with 3+ years focused on building and scaling platform solutions or infrastructure.
  • 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, with hands-on experience managing large-scale workloads on Kubernetes.
  • Expert-level proficiency in scripting and automation using Bash, Groovy, Python, or similar languages.
  • 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.
  • Extensive experience designing and implementing CI/CD pipelines, build automation, and deployment strategies.
  • Expert-level proficiency with version control workflows (Git/Bitbucket) and distributed systems monitoring using tools such as Splunk, DataDog, Dynatrace, or CloudWatch.
  • Deep understanding of OAuth 2.0, secure authentication/authorization patterns, and security best practices in platform engineering.
  • Exceptional documentation skills, including creating comprehensive technical documentation, architecture decision records (ADRs), runbooks, and system diagrams.
  • 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.

Nice to have

  • Production experience architecting, building, and scaling GraphQL platforms serving multiple teams or business units.
  • Extensive experience with AWS cloud architecture and services, including architectural patterns for high availability and disaster recovery.
  • Advanced knowledge of AWS services including EKS, ECS Fargate, IAM, VPC design, CloudWatch, X-Ray, ElastiCache-Redis, RDS Aurora Postgres, MSK, and KMS.
  • Proficiency in at least one modern programming language (Java, Rust, Go, or similar), with ability to review code and provide technical guidance.
  • Proven track record designing and implementing comprehensive observability solutions (metrics, logging, tracing, alerting) and automating complex CI/CD workflows using Jenkins, Spinnaker, or similar platforms.
  • Contributions to open-source projects or technical communities related to GraphQL, platform engineering, or cloud-native architectures.

What the JD emphasized

  • Expert in containerization and orchestration technologies such as Docker and Kubernetes, with hands-on experience managing large-scale workloads on Kubernetes.
  • Expert-level proficiency in scripting and automation using Bash, Groovy, Python, or similar languages.
  • 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.
  • Extensive experience designing and implementing CI/CD pipelines, build automation, and deployment strategies.
  • Expert-level proficiency with version control workflows (Git/Bitbucket) and distributed systems monitoring using tools such as Splunk, DataDog, Dynatrace, or CloudWatch.
  • Deep understanding of OAuth 2.0, secure authentication/authorization patterns, and security best practices in platform engineering.