Java Developer with React

Key Responsibilities

1.

Full Stack

Development

• Develop scalable, secure, and maintainable applications using Java (Spring Boot) for backend and React.js for frontend.
• Architect and implement RESTful APIs and microservices.
• Collaborate with cross-functional teams to deliver high-quality software solutions.
• Conduct code reviews, mentor junior developers, and ensure adherence to best practices.

2. Containerization & Orchestration (Docker/Kubernetes)

• Build, deploy, and manage containerized applications using Docker and Kubernetes (or OpenShift).
• Implement CI/CD pipelines for automated build, test, and deployment processes.
• Optimize distributed, containerized environments for scalability and reliability.

3. Infrastructure as Code (Terraform/CloudFormation)

• Automate cloud infrastructure provisioning and management using Terraform and/or AWS CloudFormation

  .

• Maintain infrastructure as code repositories and ensure compliance with security and governance standards.

4. Messaging & Event Streaming (Apache Kafka/MQ)

• Integrate and maintain high-throughput messaging systems like Apache Kafka or IBM MQ for event-driven architectures.
• Design and optimize messaging queues for real-time data processing and business-critical workflows.

5. Observability & Monitoring (Datadog, AppDynamics, Dynatrace)

• Instrument applications for observability using tools like Datadog

  , AppDynamics

  , or Dynatrace

  .

• Set up dashboards, alerts, and logs for proactive incident detection and troubleshooting.
• Collaborate with SRE/operations teams to ensure end-to-end monitoring and rapid incident response.

Preferred/Good-to-Have Skills

Generative AI Integration

: Experience with integrating Generative AI models (e.g., LLMs, RAG, MCP) into enterprise applications is a plus.

• Familiarity with frameworks like LangChain4j

  , Spring AI

  , or Embabel is beneficial.

• Collaboration with AI/ML teams to embed intelligent features is a good-to-have skill.
• Experience with AI/ML frameworks and vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector).
• Familiarity with Python for AI/ML integration.