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 Asset and Wealth Management Technology, you serve as a seasoned member of an agile team designing and delivering market-leading technology products in a secure, stable, and scalable way. You will help transform and build capabilities for a modern, cloud-native services and event/workflow-driven architectures, leveraging AWS managed services (e.g., Lambda and Step Functions), enabling and integrating with applications running on private cloud and of various design patterns. You will partner closely with product owners, engineers, and stakeholders to deliver resilient solutions that improve time-to-market, operational excellence, and client experience across the lending lifecycle.
Job Responsibilities
- Design, develop, and deliver scalable, resilient backend services using Java (Spring Boot) and Python.
- Build cloud-native components on AWS, leveraging managed services such as AWS Lambda and AWS Step Functions (plus related services such as API Gateway, SQS/SNS, CloudWatch as applicable).
- Design and optimize data models and queries in PostgreSQL, ensuring performance, integrity, and maintainability (schema design, indexing, migrations) and develop and maintain user-facing features using Svelte or another modern UI framework (e.g., React/Angular/Vue), integrating with backend APIs and ensuring a high-quality user experience.
- Collaborate across backend, UI, and product to translate requirements into clear UI behavior, usability, and accessibility considerations, and produce or contribute to architecture and design artifacts; ensure design constraints are met in code.
- Implement and improve CI/CD pipelines and engineering standards (code quality, security scanning, observability, deployment automation).
- Participate in end-to-end delivery, including supporting applications running in production and test environments to ensure stability, performance, and availability, and perform incident triage, troubleshooting, and root-cause analysis across services, workflows, and databases; drive fixes through to resolution and prevent recurrence.
- Improve observability (logs, metrics, traces, dashboards, alerts) and operational runbooks to reduce mean time to detect/restore and improve resilience, and contribute to engineering communities of practice and foster a culture of inclusion, accountability, and continuous learning.
- Demonstrate a learning mindset: ramp up quickly, run pragmatic experiments/spikes, and apply new technologies where they add value and use AI-assisted development techniques (where approved) to accelerate implementation (scaffolding, test creation, refactoring, documentation, troubleshooting) while validating correctness and security.