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Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Nov 2, 2026. JPMorganChase scores A on the Alion truth index.

Overview
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Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Make your mark delivering secure, scalable software with mentorship, mobility, and hands-on Java, React, and cloud engineering.

As a Software Engineer II at JPMorgan Chase within the Corporate Sector, you enhance, design, and deliver software components in a secure, stable, and scalable way. You execute software solutions through design, development, and technical troubleshooting across multiple components within a product, application, or system. You continue building the skills and experience needed to grow within your role and advance your career.

Job Responsibilities:

  • Build and maintain backend services and application programming interfaces using Java (commonly Spring and Spring Boot).
  • Develop user-facing features using React (JavaScript or TypeScript) with a focus on usability and performance.
  • Integrate artificial intelligence, machine learning, and generative artificial intelligence capabilities into applications, including model endpoint consumption, prompt and response handling, and basic evaluation and monitoring using privacy- and safety-aware design.
  • Optimize data access layers by writing efficient queries and improving performance for structured and unstructured databases.
  • Deploy, troubleshoot, and improve cloud applications on Amazon Web Services, contributing to continuous integration and continuous delivery and environment reliability.
  • Write unit and integration tests, participate in code reviews, and follow secure coding and software development life cycle best practices.
  • Collaborate with product, design, and platform partners to translate requirements into robust technical solutions.
  • Support production systems through monitoring, incident triage, and root-cause analysis.

Required qualifications, skills, and capabilities:

  • Demonstrate professional experience as a software engineer delivering production features independently with guidance on larger design.
  • Apply strong proficiency in Java and API development.
  • Build user interfaces using React.Js and modern frontend patterns such as components, state management, and routing.
  • Design database schemas, indexing strategies, and query optimization approaches with strong SQL proficiency.
  • Use Amazon Web Services services such as EC2, ECS, EKS, Lambda, S3, RDS, DynamoDB, CloudWatch, and Identity and Access Management.
  • Maintain and debug code in a large corporate environment using one or more modern programming languages and database querying languages.
  • Leverage enterprise-authorized artificial intelligence-assisted software development tools for coding, testing, troubleshooting, or documentation while critically evaluating and validating outputs.
  • Adhere to responsible artificial intelligence practices in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
  • Execute work across the full software development life cycle.
  • Follow agile ways of working, continuous integration and continuous delivery practices, application resiliency, and security.

Preferred qualifications, skills, and capabilities:

  • Implement microservices and event-driven designs using tools such as Kafka/SQS/SNS including caching patterns such as Redis.
  • Use Docker and Kubernetes, including infrastructure-as-code approaches such as Terraform and AWS CloudFormation.
  • Strengthen observability through logging, metrics, and tracing using tools such as CloudWatch and OpenTelemetry.
  • Apply patterns such as retrieval-augmented generation, embeddings, and vector search, including responsible artificial intelligence guardrails and data handling.
  • Experience with REST APIs.
  • Utilize GraphQL patterns where applicable for application programming interface development.

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