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oracle

Senior Lead Software Engineer - Java, Kafka, Cloud

JPMorgan Chase
Mumbai, IND
Full-time
Senior
Onsite
Discovered 3 weeks ago
JavaSpring BootKafkaSoftware Development Life CycleAI-assisted code reviewautomated testing
Free

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Key skills for this role

JavaSpring BootKafka
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  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Serves as a function-wide subject matter expert in one or more areas of focus
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
  • Proven expertise in building large scale & high throughput application
  • Proficient in Java, Spring Boot, Kafka & cloud native applications
  • Proficient in distributed systems and parallel processing
  • Proficient in Performance Analysis and Tuning (Working knowledge of Java based Profiling and Monitoring Tools)
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Working experience of Kafka Streams, Even Driven Architecture, Microservices Architecture
  • Good understanding of Behavior driven design
  • Understanding of Kubernetes, APIGEE gateway and cloud services
  • Working knowledge of agentic workflows
  • Proven production deliverables in agentic AI
  • Hands-on across the modern AI toolchain

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