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JPMorgan Chase & Co.

Software Engineer II - Java, UI, Spark, Kafka

JPMorgan Chase & Co. · Mumbai, Maharashtra, India

Financial Services · 10,001+ employees

5 h ago
Mid (2-5 yrs) Full-time India
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About the role

You will design, build, and maintain end-to-end full-stack solutions using Java and modern UI frameworks while collaborating with agile teams. Additionally, you will troubleshoot complex production issues and integrate data platforms to expose reliable datasets to consumers.

What they look for

Java Spring Boot React Angular Vue TypeScript JavaScript SQL PostgreSQL Oracle Kafka Spark Git CI/CD REST GraphQL

Requirements

Candidates must have 2+ years of applied software engineering experience with proficiency in Java, backend development, and modern frontend frameworks. Strong knowledge of relational databases, engineering practices like CI/CD, and experience with AI-assisted development tools is required.

Full description

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II - Java Full Stack Developer at JPMorgan Chase within the Commercial & Investment Bank, you'll be a part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job responsibilities

  • Design, build, and maintain end-to-end full-stack solutions using Java technologies and modern UI frameworks.
  • Develop and support backend services and APIs (REST/GraphQL as applicable), including authentication/authorization, integration patterns, and error handling.
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
  • 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
  • Build responsive, accessible frontend experiences and reusable UI components aligned to engineering standards.
  • Enable data-centric use cases by integrating with data platforms, data services, and event streams to expose reliable datasets and metrics to upstream/downstream consumers.
  • Collaborate with the data horizontal team to improve data quality, observability, lineage, and governance where required by the applications.
  • Apply strong engineering practices: code reviews, unit/integration testing, CI/CD, performance tuning, and production support.
  • Contribute to system design discussions and drive non-functional requirements (security, resiliency, scalability, latency).
  • Troubleshoot complex production issues across UI, services, and data interactions; implement sustainable fixes and automation.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 2+ years applied experience
  • Professional software engineering experience with significant full-stack delivery.
  • Strong proficiency in Java and enterprise backend development (e.g., Spring / Spring Boot).
  • Experience building microservices and well-designed APIs (REST).
  • Solid understanding of frontend development with at least one modern framework (e.g., React, Angular, or Vue) plus HTML/CSS/TypeScript/JavaScript.
  • Strong knowledge of relational databases and SQL (e.g., PostgreSQL/Oracle), including schema design and query optimization.
  • Hands-on experience with engineering practices such as CI/CD pipelines, automated testing, and source control (Git).
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
  • Practical knowledge of security concepts (OAuth2/JWT, secure coding, secrets management) and production readiness.
  • Strong problem-solving skills, ability to work across teams, and excellent written/verbal communication.

Preferred qualifications, capabilities, and skills

  • Experience with data engineering and data platform integrations, such as: Messaging/streaming: Kafka (or equivalent), Data processing: Spark (or equivalent), Data warehousing/lakes: Snowflake/Databricks/Hive (or similar), Orchestration: Airflow (or similar)
  • Familiarity with data governance concepts: metadata/lineage, data quality checks, access controls, and auditability.
  • Experience with observability tooling: centralized logging, metrics, tracing (e.g., OpenTelemetry concepts).
  • Containerization and orchestration: Docker and Kubernetes (or equivalent).
  • Domain exposure to loan origination / servicing systems or regulated financial workflows (helpful but not required).