Job Summary (in list format):
- Design, develop, test, and maintain Java-based enterprise applications and APIs.
- Build and support application components using EJB and Spring/Spring Boot frameworks.
- Develop data access layers and optimize queries for Oracle DB; implement document models and queries for MongoDB.
- Implement and tune Redis caching strategies (e.g., read/write-through caching, TTL policies, cache invalidation).
- Integrate Agentic AI capabilities, including agent orchestration, tool/function calling, and observability features.
- Write clean, maintainable, and secure code following SDLC best practices.
- Troubleshoot production issues, perform root-cause analysis, and implement fixes and performance improvements.
- Collaborate with architects, QA, DevOps, and product stakeholders to deliver end-to-end features.
- Create technical documentation, including design notes, runbooks, and API documentation, and support knowledge transfer.
- Required to have strong experience in Core Java, OOP, Collections, Concurrency, and Kafka.
- Must have hands-on experience with EJB (stateless/stateful beans, transactions, JPA integration).
- Proficient in Spring Framework (Spring Boot, Spring MVC, Spring Data).
- Solid experience working with Oracle DB (SQL, PL/SQL basics, performance tuning, indexing).
- Experience with MongoDB (schema design, aggregation pipeline, indexing, performance).
- Experience implementing Redis as a cache (data structures, eviction policies, clustering/sentinel awareness is a plus).
- Familiarity with RESTful APIs, JSON, and integration patterns.
- Working knowledge of Agentic AI concepts and implementation patterns.
- Typically requires 4+ years of relevant development experience in Kafka, Java, SQL/PL-SQL, and AWS.
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- Design, develop, test, and maintain Java-based enterprise applications and APIs.
- Build and support application components using EJB and Spring/Spring Boot frameworks.
- Develop data access layers and optimize queries for Oracle DB; implement document models and queries for MongoDB.
- Implement and tune Redis caching strategies (e.g., read/write-through caching, TTL policies, cache invalidation).
- Integrate Agentic AI capabilities, including agent orchestration, tool/function calling, and observability features.
- Write clean, maintainable, and secure code following SDLC best practices.
- Troubleshoot production issues, perform root-cause analysis, and implement fixes and performance improvements.
- Collaborate with architects, QA, DevOps, and product stakeholders to deliver end-to-end features.
- Create technical documentation, including design notes, runbooks, and API documentation, and support knowledge transfer.
- Required to have strong experience in Core Java, OOP, Collections, Concurrency, and Kafka.
- Must have hands-on experience with EJB (stateless/stateful beans, transactions, JPA integration).
- Proficient in Spring Framework (Spring Boot, Spring MVC, Spring Data).
- Solid experience working with Oracle DB (SQL, PL/SQL basics, performance tuning, indexing).
- Experience with MongoDB (schema design, aggregation pipeline, indexing, performance).
- Experience implementing Redis as a cache (data structures, eviction policies, clustering/sentinel awareness is a plus).
- Familiarity with RESTful APIs, JSON, and integration patterns.
- Working knowledge of Agentic AI concepts and implementation patterns.
- Typically requires 4+ years of relevant development experience in Kafka, Java, SQL/PL-SQL, and AWS.
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