JPMorgan Chase—Software Engineer III-Java, Kubernetes

Job description

Description: 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. 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 - 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 approaches - Experience with service mesh technologies (Istio, Linkerd) — traffic routing, header-based request matching, and traffic splitting - Experience with test data management — snapshot/restore automation, data masking, synthetic data generation - Familiarity with developer experience tooling — CLIs, developer portals (Backstage), API documentation, and self-service workflows - Experience with container networking, cross-cluster communication, or hybrid cloud/on-premises connectivity patterns