Software Engineer III - Java, microservice, AWS, Databricks, MLOps

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 JPM - US Wealth Management Tech , 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
- Design, develop, and maintain Java-based backend services and python based Databricks applications.
- Build and integrate REST APIs and event-driven services.
- Apply resilient microservice design practices, including service decomposition and inter-service communication.
- Deploy and support applications on AWS.
- Write and maintain automated tests, participate in code reviews, and help troubleshoot production issues.
- Collaborate with product, design, and engineering partners throughout delivery demonstrating end-to-end ownership.
- 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.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience in full stack/software engineering roles with strong Java, Microservices, Messaging, React, and AWS fundamentals.
- Hands-on Java experience, including Core Java, object-oriented design, collections, and concurrency.
- Experience building and supporting microservices and REST APIs. Deep knowledge of microservice architecture: service decomposition, inter-service communication, resilience patterns
- Experience with messaging or event-streaming technologies such as Kafka or RabbitMQ. Experience deploying or operating applications on AWS, using relevant services such as EC2, Lambda, S3, ECS/EKS, or API Gateway.
- Understanding of relational or NoSQL databases and secure software development practices.
- Proficient in Python for scripting, automation, and backend/data processing tasks. Exposure to Databricks for data engineering/analytics workloads.
- Observability practices, including logging, metrics, and distributed tracing; familiarity with tools such as ELK, Prometheus, Grafana, or CloudWatch.
- DevOps practices — Production monitoring, alerting, and reliability practices. CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), and infrastructure as code.
- Familiarity with MLOps practices — model deployment, monitoring, versioning, CI/CD for ML pipelines. Experience with containerization (Docker) and orchestration (Kubernetes).
- 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.