Key Responsibilities

- Design, develop, and maintain scalable backend applications using Java and Spring Boot.
- Develop RESTful and GraphQL APIs for enterprise-grade applications.
- Build and maintain microservices-based architectures with a focus on scalability, security, and performance.
- Implement event-driven solutions using Apache Kafka for asynchronous communication.
- Develop and optimize MongoDB database schemas, queries, and aggregation pipelines.
- Containerize applications using Docker and deploy services in cloud environments.
- Build, deploy, and maintain applications on AWS services such as EC2, ECS/EKS, Lambda, API Gateway, S3, RDS, CloudWatch, IAM, and VPC.
- Integrate AI-enabled applications using Model Context Protocol (MCP) where applicable.
- Collaborate with frontend developers, product owners, architects, and DevOps teams to deliver high-quality solutions.
- Write clean, maintainable, testable, and well-documented code.
- Participate in code reviews and mentor junior developers.
- Troubleshoot production issues and optimize application performance.
- Follow Agile/Scrum development methodologies and participate in sprint ceremonies.

Required Skills

- 6+ years of experience in backend application development.
- Strong proficiency in Java (Java 11/17 or above).




- Extensive experience with Spring Boot and the Spring ecosystem.
- Solid understanding of Microservices Architecture.
- Experience with Apache Kafka for messaging and event streaming.
- Strong knowledge of Docker and containerized deployments.
- Hands-on experience with AWS cloud services.
- Experience designing and consuming GraphQL APIs.
- Strong experience with MongoDB and NoSQL database design.
- Good understanding of REST APIs and API security (OAuth2, JWT).
- Experience with Git and up-to-date CI/CD pipelines.
- Strong understanding of object-oriented programming, design patterns, and SOLID principles.
- Familiarity with unit testing frameworks such as JUnit and Mockito.

Preferred Skills

- Experience with Kubernetes (EKS/OpenShift) is a plus.
- Knowledge of Terraform or Infrastructure as Code.
- Experience with Redis or caching mechanisms.
- Exposure to Elasticsearch/OpenSearch.
- Familiarity with observability tools such as Prometheus, Grafana, ELK, or Splunk.
- Experience implementing AI integrations using MCP (Model Context Protocol), AI agents, or LLM-based applications.
- Knowledge of secure coding practices and application security.

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