Senior Software Engineer – Java Developer

6 days ago

Bengaluru, Karnataka, India NMS Consultant Full time ₹ 1,04,000 - ₹ 1,30,878 per year

Job Title - Senior Software Engineer – Java Developer

Experience - 6+ Years

Location - Bangalore

Job Description

Experienced Senior Core Java Developer to design, develop and optimize 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

 Lead the design and development of 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.

 Oversee cloud-native deployments and manage environments on AWS/Azure/GCP.

Preferred 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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