What are the responsibilities and job description for the Java Developer position at Jobs via Dice?
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Must have:
Java-based microservices Spring Boot, Spring Cloud, and Hibernate (Java Software Developer)
Frontend React or Angular
Natural Language Systems (NLS), integrating with NLP APIs, LLMs, and AI models
Relational database (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Elasticsearch)
Message brokers (Kafka, RabbitMQ)
Performance testing using JUnit, Mockito, and TestContainers.
Requirements:
Key Responsibilities:
Develop and maintain Java-based microservices using Spring Boot, Spring Cloud, and Hibernate.
Implement and optimize Natural Language Systems (NLS), integrating with NLP APIs, LLMs, and AI models.
Design RESTful APIs and ensure seamless system communication using GraphQL, gRPC, or WebSockets.
Collaborate with AI/ML engineers to enhance text processing, speech-to-text, and chatbot applications.
Work with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Elasticsearch) for efficient data storage and retrieval.
Utilize message brokers (Kafka, RabbitMQ) for event-driven architectures.
Optimize code for high performance, scalability, and security following best practices.
Conduct unit, integration, and performance testing using JUnit, Mockito, and TestContainers.
Troubleshoot, debug, and enhance system reliability in a CI/CD pipeline (Jenkins, GitHub Actions, Docker, Kubernetes).
Requirements:
7 years of hands-on experience in Java development with Spring Boot framework.
Proficiency in JavaScript and front-end frameworks (React, Angular, or similar)
Proficiency in Natural Language Systems (NLS), including NLP processing and AI model integration.
Experience in building scalable, distributed systems and microservices architecture.
Strong knowledge of RESTful APIs, GraphQL, WebSockets, and API security protocols (OAuth, JWT, SAML).
Familiarity with AI/ML frameworks like TensorFlow, PyTorch, or OpenAI APIs is a plus.
Experience working with containerized applications (Docker, Kubernetes, Helm charts).
Understanding of DevOps practices, including CI/CD, monitoring, and cloud deployments (AWS, Google Cloud Platform, or Azure).
Knowledge of text analytics, entity recognition, speech processing, and chatbot development is a strong advantage.
Strong problem-solving skills and ability to work in Agile/Scrum teams
Must have:
Java-based microservices Spring Boot, Spring Cloud, and Hibernate (Java Software Developer)
Frontend React or Angular
Natural Language Systems (NLS), integrating with NLP APIs, LLMs, and AI models
Relational database (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Elasticsearch)
Message brokers (Kafka, RabbitMQ)
Performance testing using JUnit, Mockito, and TestContainers.
Requirements:
Key Responsibilities:
Develop and maintain Java-based microservices using Spring Boot, Spring Cloud, and Hibernate.
Implement and optimize Natural Language Systems (NLS), integrating with NLP APIs, LLMs, and AI models.
Design RESTful APIs and ensure seamless system communication using GraphQL, gRPC, or WebSockets.
Collaborate with AI/ML engineers to enhance text processing, speech-to-text, and chatbot applications.
Work with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Elasticsearch) for efficient data storage and retrieval.
Utilize message brokers (Kafka, RabbitMQ) for event-driven architectures.
Optimize code for high performance, scalability, and security following best practices.
Conduct unit, integration, and performance testing using JUnit, Mockito, and TestContainers.
Troubleshoot, debug, and enhance system reliability in a CI/CD pipeline (Jenkins, GitHub Actions, Docker, Kubernetes).
Requirements:
7 years of hands-on experience in Java development with Spring Boot framework.
Proficiency in JavaScript and front-end frameworks (React, Angular, or similar)
Proficiency in Natural Language Systems (NLS), including NLP processing and AI model integration.
Experience in building scalable, distributed systems and microservices architecture.
Strong knowledge of RESTful APIs, GraphQL, WebSockets, and API security protocols (OAuth, JWT, SAML).
Familiarity with AI/ML frameworks like TensorFlow, PyTorch, or OpenAI APIs is a plus.
Experience working with containerized applications (Docker, Kubernetes, Helm charts).
Understanding of DevOps practices, including CI/CD, monitoring, and cloud deployments (AWS, Google Cloud Platform, or Azure).
Knowledge of text analytics, entity recognition, speech processing, and chatbot development is a strong advantage.
Strong problem-solving skills and ability to work in Agile/Scrum teams