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 JPMorganChase within the Consumer and Community Banking, 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 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
- Certifications: AWS Associate Architect/Developer; Certified Kubernetes Application Developer (CKAD).
- Design and develop efficient, unit-tested code aligned to business requirements.
- Ensure reliability, scalability, and performance for AI-assisted applications and platform operations.
- Design and implement AI-driven AIOps solutions (intelligent alerting, noise reduction, auto-correlation).
- 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
- Build and maintain observability (monitoring, alerting, telemetry) for AI platforms and applications.
- Build and support automation for anomaly detection, alerting, and self-healing workflows.
- Drive delivery and operational excellence by defining/executing the AI-assisted SRE roadmap, mentoring engineers, managing dependencies, and partnering with global stakeholders while meeting SLAs, compliance, and business requirements.
Required qualifications, capabilities, and skills
- Software engineering foundation: Formal training/certification with 5+ years applied experience; strong Agile delivery and ability to multitask/operate independently.
- Java expertise: Core/EE with Spring Boot, Spring MVC, Spring Cloud (build and support microservices/distributed systems).
- SRE/DevOps/Platform Engineering: Demonstrated hands-on experience improving reliability, operations, and platform capabilities.
- AWS cloud proficiency: Strong hands-on across ECS, Lambda, API Gateway, Bedrock, CloudWatch, RDS, EKS and broader AWS infrastructure solutions.
- 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
- LLM integrations: Hands-on experience with AWS and LLM APIs.
- Observability: Expertise with OpenTelemetry, Grafana, Prometheus, ELK, CloudWatch.
- Delivery engineering: CI/CD tooling (GitHub Actions, Jenkins, Spinnaker; Git/Bitbucket, Maven, Sonar) plus scripting (Bash/PowerShell) and testing frameworks (JUnit, Selenium, Cucumber, Mockito).
- Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
