High-Performance Backend Expert

1 day ago

Bengaluru, Karnataka, India beBeeBackend Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Title:

Senior Software Engineer - A High-Performance Backend Expert

About the Role:

We are seeking an experienced Senior Core Java Developer to lead the design, development, and optimization of 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:

  1. Lead the design and development of robust Core Java applications (Standalone, Microservices, and Batch Processing).
  2. Architect and optimize scalable RESTful APIs for enterprise-grade systems.
  3. Drive performance tuning, memory management, multi-threading, and concurrency improvements.
  4. Collaborate with cross-functional teams, including frontend (ReactJS) and DevOps, for end-to-end delivery.
  5. Design, implement, and optimize SQL/NoSQL databases for large-scale, high-volume datasets.
  6. Build and lead data analytics pipelines to extract actionable insights from structured and unstructured data.
  7. Integrate AI/ML models into production systems to enable intelligent automation and predictive capabilities.
  8. Ensure adherence to coding standards, performance benchmarks, and security best practices.
  9. Mentor junior engineers and participate in technical reviews, architecture discussions, and roadmap planning.
  10. Oversee cloud-native deployments and manage environments on 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.

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