
at J.P. Morgan
Bulge Bracket Investment BanksPosted 8 days ago
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**Software Engineer III - Java Full Stack/React** in Mumbai, India. Designs and delivers reliable, secure, and scalable products. Key responsibilities include full-stack development (Spring Boot, Hibernate/JPA, Kafka, ReactJS), system design, technical troubleshooting, and contributing to software engineering communities. Leverages AI coding assist tools to improve code quality and productivity. Requires 3+ years of experience, proficiency in software engineering fundamentals, and familiarity with enterprise AI-assisted tools. preferably with cloud technology and modern front-end experience.
- Compensation
- Not specified
- City
- Mumbai
- Country
- India
Currency: Not specified
Full Job Description
Location: Mumbai, Maharashtra, India
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 JPMorgan Chase within the Commercial & Investment Bank Payments Technology team, you will be an experienced member of an agile team, tasked with designing and delivering reliable, market-leading technology products that are secure, stable, and scalable.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
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
Required qualifications, capabilities, and skills
- 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
- Proven experience with Spring Boot (REST APIs, configuration, dependency injection, testing), Hibernate/JPA (ORM, performance tuning, query optimization) and, Kafka (event-driven architecture, message patterns, retry/error handling)
- Working knowledge of ReactJS or similar JavaScript frameworks (enough to contribute meaningfully when needed)
- Hands-on knowledge of Docker and Kubernetes (deployments, services/ingress, config/secrets, scaling, basic troubleshooting).
- Strong understanding of software engineering fundamentals: OOP, design patterns, data structures, concurrency, and API design
- Microservices architecture, distributed systems, and resiliency patterns (circuit breakers, bulkheads, idempotency).
- Observability tooling (metrics, logs, tracing) such as Prometheus/Grafana, ELK/OpenSearch, Splunk, OpenTelemetry
Security best practices (OWASP, secrets management, authentication/authorization)
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
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
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