High-Performance Backend Software Engineer

3 days ago

Madurai, Tamil Nadu, India beBeeCoreJava Full time ₹ 15,00,000 - ₹ 20,00,000
Senior Core Java Developer Job Description

We are seeking a skilled and experienced Senior Core Java Developer to join our team. As a key member of the development team, you will be responsible for designing, developing and optimizing high-performance backend applications, services and APIs.

The ideal candidate will have expertise in Java, database architecture, data analytics and AI/ML integration. This role involves driving architectural decisions, mentoring team members and delivering scalable, data-driven solutions leveraging technologies like Kafka, Spark, Redis, ReactJS, PostgreSQL, MongoDB and Cloud Services (AWS/Azure/GCP).

Key Responsibilities:
  • Design and develop robust Core Java applications (Standalone, Microservices and Batch Processing).
  • Architect and optimize scalable RESTful APIs for enterprise grade systems.
  • Drive performance tuning, memory management, multi-threading and concurrency improvements.
  • Collaborate with cross-functional teams, including frontend (ReactJS) and DevOps, for end-to-end delivery.
  • Design, implement and optimize SQL/NoSQL databases for large-scale, high-volume datasets.
  • Build and lead data analytics pipelines to extract actionable insights from structured and unstructured data.
  • Integrate AI/ML models into production systems to enable intelligent automation and predictive capabilities.
  • Ensure adherence to coding standards, performance benchmarks and security best practices.
  • Mentor junior engineers and participate in technical reviews, architecture discussions and roadmap planning.
Required Skills and Qualifications:
  • Expert-level Core Java (collections, streams, concurrency, JVM internals).
  • Proven experience with Spring Boot, Microservices and distributed system architectures.
  • Advanced database skills - schema design, indexing, query optimization and performance tuning.
  • Strong knowledge of event-driven architecture (Kafka), caching (Redis) and big data frameworks (Spark).
  • Proficiency in AI/ML model lifecycle - development, training, deployment and inference.
  • Familiarity with data visualization and analytics tools (Apache Superset, Power BI, Tableau).
  • Understanding of cloud-native architectures (Docker, Kubernetes, serverless) and CI/CD pipelines.

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