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Core Java Development Leader

3 weeks ago

Aurangabad, Maharashtra, India beBeeSoftware Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Senior Software Engineer - Java Developer

As a seasoned Senior Software Engineer – Java Developer, you will be responsible for leading the development of high-performance backend applications and services.

Key to success in this role is expertise in Java, database architecture, data analytics, and AI/ML integration. You will work closely with cross-functional teams to drive architectural decisions and deliver scalable solutions leveraging technologies like Kafka, Spark, Redis, ReactJS, PostgreSQL, MongoDB, and Cloud Services (AWS/Azure/GCP).

Responsibilities include:

  • 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 frontend (ReactJS) and DevOps teams 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
  • Oversee cloud-native deployments and manage environments on AWS/Azure/GCP

Required Skills:

  • 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