Software Engineer III - Full Stack

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III - Full Stack at JPMorgan Chase within the Commercial & Investment Bank, 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 will also be a hands-on engineer on an Agile team building and operating Spring Boot microservices running on AWS (ECS Fargate or EKS) with Oracle and PostgreSQL (RDS), and a modern web UI built with React. You will design, develop, test, deploy, and support services in a secure, resilient, and observable production environment. 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 - Execute software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems - Design, build, and maintain full-stack features across UI and backend services (React or Java 17 / Spring Boot). - Develop and operate microservices including API design, service decomposition, and reliability patterns (timeouts, retries, idempotency, DLQs). - Build integrations using AWS services such as API Gateway, SQS, SNS, S3, and RDS ; troubleshoot production issues across services and infrastructure. - Produce clear design/architecture artifacts (service boundaries, data flows, sequence diagrams, ADRs) and ensure implementation aligns with design constraints. - Improve engineering quality through code reviews, automated testing, CI/CD, and secure coding practices; contribute to operational excellence (metrics, logs, tracing, runbooks). - 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. - Create secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems - Proactively identify hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture - Add to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills - Formal training or certification on software engineering concepts and 3+ years applied experience - Proficiency with React (TypeScript, component architecture, state management, performance fundamentals). - Strong experience with Java 17+ and Spring Boot , including Spring Data JPA / Hibernate (entity modeling, transactions, performance considerations like N+1, pagination). - Hands-on deployment/operations with AWS ECS Fargate or Kubernetes/EKS , and strong container skills with Docker (image builds, runtime config, troubleshooting). - Practical experience with API Gateway, SQS, SNS, S3 , and relational databases on RDS . - Proven experience with Oracle and PostgreSQL (schema design, indexing, query tuning, migrations). - Experience with CI/CD , automated testing (unit/integration), observability (logs/metrics/traces), and application security (authn/authz basics, secrets handling, dependency scanning). - 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. - Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages - Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g. cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications, capabilities, and skills - Experience with event-driven architectures and message processing patterns (idempotency, DLQ handling, backoff/retry strategies) - Infrastructure-as-Code exposure (e.g., Terraform/CloudFormation/CDK) and production operations experience (incident response, on-call, postmortems) - API design maturity (OpenAPI/Swagger, backward compatibility/versioning, contract testing) - Performance tuning experience across UI, JVM, and database layers - Strong grounding in OOP, design patterns, and microservices best practices