JPMorganChase
Software Engineer III - Java, microservice, AWS, Databricks, MLOps
Be an Early Applicant
Designs, develops, and supports Java backend services and Python-based Databricks applications. Builds REST APIs, event-driven microservices, and AWS deployments while applying resilient architecture practices. The role includes automated testing, code reviews, production troubleshooting, observability, DevOps, CI/CD, containerization, Kubernetes, infrastructure as code, and MLOps. Collaborates with product, design, and engineering teams, uses approved AI-assisted development tools responsibly, and validates AI-generated code for quality, performance, security, and reliability.
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
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.
JPMorganChase Mumbai, Maharashtra, IND Office
B11, B9, B10, Nirlon Knowledge Park, near Mrinal Tai Gore Flyover, Cama Industrial Estate, Mumbai, Maharashtra, India, 400063
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