Software Engineer III - Java / Python with Drools
JPMorgan Chase & Co. · Bengaluru, Karnataka, India
Financial Services · 10,001+ employees
About the role
You will design and deliver secure, scalable technology products as a member of an agile team. Responsibilities include executing software solutions, maintaining high-quality production code, and leveraging AI-assisted tools to improve development productivity.
What they look for
Requirements
Candidates must have at least 3 years of applied software engineering experience with strong proficiency in Java and Drools. Practical experience in system design, debugging, and working within a large corporate environment is required.
Full description
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 Enterprise Technology, 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
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- 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.
- Strong Java development experience (e.g., Spring/Spring Boot, REST APIs, JVM performance basics).
- Strong Drools experience (authoring DRL/rules, troubleshooting firing behavior, designing fact models).
- Working Python experience for automation, scripting, data handling, and service integration.
- Familiarity with data modeling and integrating rules with upstream/downstream systems (DBs, queues, APIs).
- Strong debugging skills across application code + rules (explaining “why a rule fired/didn’t fire”).
Preferred qualifications, capabilities, and skills
- Experience with DMN and decision modeling (Drools/other), decision tables, and rule governance workflows.
- Experience in regulated domains (financial services, insurance, healthcare) and audit/traceability needs.
- Exposure to event streaming (Kafka), caching (Redis), and containerization (Docker/Kubernetes).