Software Engineer III - Java Full Stack Developer + GenAI / LLM + AWS
JPMorgan Chase · Posted Oct 15
Global banking, investment, credit card, mortgage, and asset management services
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About the role
The role sits within JPMorgan Chase's Commercial & Investment Bank, where agile teams design and deliver trusted market-leading technology products in a secure, stable, and scalable way. The work spans full-stack engineering, cloud-native microservices and APIs, and AI-driven capabilities including LLM-based services and workflow orchestration. As a Software Engineer III, you will design and develop solutions primarily in Java, Spring Boot, and Python on AWS, build microservices and Camunda-based orchestration, and drive observability, automation, and responsible AI use across the SDLC.
What you will do
- Design and develop full-stack software solutions using modern engineering approaches and patterns.
- Build and integrate AI-driven capabilities, including LLM-based services, orchestration, and workflow integrations.
- Develop and maintain cloud-native microservices and APIs (REST/streaming) with strong focus on scalability, resilience, and security controls.
- Identify and automate solutions for recurring operational issues to improve system stability and observability (logs/metrics/tracing).
- Collaborate in a Scrum/Agile team, participate in ceremonies, and contribute to a culture of diversity, opportunity, and inclusion.
- Implement solutions primarily using Java, Spring Boot, and Python (AWS Lambda), building microservices and Camunda workflow orchestration deployed on AWS ECS, backed by PostgreSQL.
- 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.
- 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.
Skills used in this role
What the employer is looking for
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Strong application development skills with exposure to operational stability in production environments and hands-on experience in Java Full Stack Development.
- Experience with system design fundamentals, microservices patterns, and API development (RESTful and/or streaming).
- Experience with distributed systems and at least one major cloud platform (AWS, GCP, or Azure)
- Proficiency with data technologies (relational and/or NoSQL) and common observability practices.
- Practical familiarity with LLMs / generative AI concepts and use cases (e.g., RAG, tool/prompt orchestration, guardrails/evaluation); working knowledge of Python for AI/ML integrations.
- Overall knowledge of the Software Development Life Cycle, and solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
- Familiarity with Docker, Kubernetes, Helm, modern CI/CD practices, multi-region service deployments, and zero-downtime release strategies.
- Strong communication skills, ownership mindset, proactive approach to continuous improvement, and a track record delivering scalable, reliable, and secure products from concept to launch.
- 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.
Preferred qualifications
- Cloud certification in AWS, GCP, or Azure.
- Working knowledge of Python (for AI/ML integrations) is a plus.
- Familiarity with Docker, Kubernetes, Helm, and modern CI/CD practices.
- Experience with multi-region service deployments and zero-downtime release strategies.
- Strong communication skills, ownership mindset, and a proactive approach to continuous improvement.
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
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