Software Engineer III,Python/AWS, AWS,CI/CD, Kubernetes

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.

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