Live opening · Posted 3 days ago
At a glance
The key details from the original listing.
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About the role
Description supplied by the original job listing.
Core Engineering:
• Design, develop, and maintain scalable backend services and APIs.
• Build high-performance distributed systems using Java/J2EE.
• Own features end-to-end from design to deployment and monitoring.
• Optimize applications for performance, scalability, and reliability.
• Write clean, maintainable code with proper unit and automation tests.
• Collaborate with Product, Design, and QA teams to deliver product features.
• Strong analytical skills with excellent logical reasoning and coding abilities.
AI & Modern Tech Initiatives (Recent Trends):
• Use AI-assisted development tools (Copilot, ChatGPT, Claude, Codex, Cursor, etc.) for coding, debugging, and documentation.
• Integrate generative AI and Large Language Models (LLMs) into backend services using modern Java AI frameworks like Spring AI or LangChain4j.
• Design and implement Retrieval-Augmented Generation (RAG) workUlows by connecting Java applications with Vector Databases (e.g., Pinecone, Milvus, Qdrant).
• Build AI-driven APIs and robust orchestration layers to manage prompts and context windows efUiciently.
• 2–5 years of backend development experience.
• Strong expertise in Java / J2EE, Springboot, KaUka and React technologies.
• Solid understanding of Data Structures and Algorithms.
• Knowledge of multithreading, memory management, and system design.
• Experience with MySQL or PostgreSQL, NoSql database.
• Strong SQL query writing (SELECT, JOINs, GROUP BY, subqueries, CTEs)
• Window functions (ROW_NUMBER, RANK, etc.) and Views
• Basic stored procedures/functions
• Query optimization fundamentals
• Basic indexing concepts and understanding of execution plans (EXPLAIN)
• Transaction management (ACID, isolation levels)
• Familiarity with MongoDB and RESTful Web Services.
AI & Tech Enhancements:
• Experience using AI-powered development tools is a plus.
• Basic understanding of prompt engineering, model temperature tuning, and token optimization.
• Experience with cloud-native development, including containerization (Docker, Kubernetes) and CI/CD pipelines.
Employment type
Full-time
Work arrangement
No
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