
Software Engineer III - Java Developer + Python + AI + Elastic search
JPMC · Mumbai, Maharashtra, India
Strong hiring record · median 28 days open
Hiring signal
Actively hiring
Posted 4 days ago · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted 4 days ago
- Still listed on the employer's own board
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III - Java Developer + Python + AI + Elastic search at JPMorgan Chase within the Commercial & Investment Bank, you'll 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
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develops secure high-quality production code (primarily Java / Spring Boot), and reviews and debugs code written by others
- Leads the design and delivery of scalable microservices/APIs within the Spring ecosystem (e.g., Spring MVC/WebFlux, Spring Data, Spring Security), with strong testing practices
- Proactively improves engineering productivity using AI4Tech practices, including hands-on use of Copilot/Claude Code for refactoring, test generation, documentation, and code modernization—while ensuring correctness and secure coding standards
- Builds and operationalizes AI agents that integrate with engineering workflows (e.g., PR review assistants, runbook/support agents, remediation assistants), including tool/function calling, structured outputs, and safety/guardrails
- Uses Python as needed for AI/agent prototyping, automation, evaluation harnesses, or glue code/integrations
- 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
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced Java development experience with strong fundamentals (OO design, concurrency, performance, debugging)
- Strong hands-on experience with Spring Boot and related frameworks (REST APIs, security, persistence), Elastic search, plus unit/integration testing.
- AI4Tech hands-on experience using Copilot/Claude Code (or similar approved tools) to accelerate delivery while maintaining code quality, security, and test coverage
- Experience building AI agents / LLM-enabled workflows, including prompt discipline, grounding/verification strategies, and safe handling of sensitive data
- Some experience or working knowledge of Python (scripting, automation, or AI/agent prototyping)
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Practical experience on 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.
Preferred qualifications, capabilities, and skills
- Experience designing and operating production-grade agentic systems (observability, evals, prompt/versioning, fallbacks, rate limits, and guardrails)
- Experience with modern microservice patterns (resiliency, distributed tracing, event-driven design)
Skills
- Java
- Python
- Elastic
- Spring Boot
- Spring
- Spring MVC
- Webflux
- Spring Data
- Spring Security
- GitHub Copilot
- Claude Code
- LLM
- Kubernetes
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