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Senior Software Engineer - Java Technologies

NMS Consultant
Bangalore
6 - 10 Years
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4.6white-divider10+ Reviews

Posted on: 12/09/2025

Job Description

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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