The posting
Responsibilities
- Design, develop, and maintain scalable Java and Spring Boot microservices for distributed, cloud-based enterprise applications.
- Develop and integrate secure, scalable REST APIs using Java, Spring Boot, JPA/Hibernate, and OAuth.
- Develop and deploy scalable applications across AWS, leveraging services such as Amazon EKS, S3, RDS, DynamoDB, Lambda, EMR, and Step Functions.
- Develop and support data-intensive applications and data engineering pipelines using Snowflake, AWS EMR, Hadoop, Hive,and Trino.
- Build and integrate AI/data solutions involving AWS Bedrock, OpenSearch, vector-based retrieval, and RAG workflows.
- Develop containerized applications using Docker and Kubernetes/EKS and support deployment across cloud environments.
- Implement and maintain CI/CD pipelines using Jenkins and Git-based workflows.
- Develop and optimize data-access components using JPA/Hibernate, integrating Java applications with relational and NoSQL database systems.
- Develop scalable, secure, and multi-tenant backend services with emphasis on performance, reliability, and maintainability.
- Participate in architecture discussions, code reviews, technical design, troubleshooting, and Agile development practices.
Requirements
- 8+ years of professional software development experience, with strong hands-on experience in Java backend development.
- Strong hands-on experience in Java and Spring Boot, with substantial experience developing microservices-based distributed systems.
- Hands-on experience building and supporting scalable solutions within AWS, with exposure to services such as Amazon EKS, S3, DynamoDB, RDS, Lambda, EMR, and Step Functions.
- Hands-on experience with Snowflake and enterprise-scale data engineering/data platform environments.
- Experience with AWS Bedrock, Generative AI, RAG, OpenSearch, or vector-based retrieval technologies.
- Strong experience with Docker and Kubernetes, preferably Amazon EKS.
- Experience building scalable REST APIs and implementing OAuth2-based authentication and authorization.
- Practical experience working with DynamoDB, MongoDB, PostgreSQL and MySQL with an understanding of data modeling, querying, and performance optimization.
- Experience with AWS EMR, Hadoop, Hive, or Trino for large-scale data processing.
- Experience with Jenkins and CI/CD practices for automated build and deployment pipelines.
- Experience in Python for data engineering, automation, or AI/analytics workflows.
- Experience with distributed systems, cloud-native architecture, containerization, and scalable backend design.
- AWS Certification is preferred.



