Software Engineer III-Java, Kubernetes

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 Commercial & Investment Bank Payments Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems 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. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills A. Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability Understanding of distributed systems fundamentals — networking, service discovery, DNS, load balancing, and the operational challenges of multi-service architectures 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. Strong proficiency in Go, Rust, or Java — writing production-grade, well-tested, maintainable code for platform services operating at scale Solid experience with Kubernetes — including deployments, namespaces, services, ingress, ConfigMaps/Secrets, and familiarity with custom controllers or operators Hands-on experience with infrastructure-as-code (Terraform, Ansible) — writing modules, managing state, and provisioning infrastructure repeatably across environments Experience with at least several of the following data technologies in an automation context: Oracle, PostgreSQL, MongoDB, CockroachDB, Cassandra, Kafka, DynamoDB Experience building or extending CI/CD pipelines (Jenkins, Spinnaker, GitHub Actions, or Argo CD) — including custom stages, shared libraries, and webhook integrations Preferred qualifications, capabilities, and skills Experience with environment provisioning systems, namespace-per-PR patterns, or composable/virtual environment