REQUIREMENTS:
- 6 years of Java development experience (Java 17 preferred).
- Strong experience with Spring Boot 3.x Spring Data and Spring Security.
- Hands-on experience with the Spring AI project (ChatClient EmbeddingClient VectorStore).
- Strong understanding of LLM concepts: tokens temperature model architectures.
- Experience implementing RAG and working with vector databases.
- Experience with vector stores like Pinecone Weaviate pgvector etc.
- Experience with SQL/NoSQL databases and integrating them into enterprise apps.
- Familiarity with Docker Kubernetes and CI/CD pipelines.
- Experience integrating AI providers (OpenAI Azure AI Anthropic) into enterprise systems.
- Strong problem-solving and architectural skills for production-grade AI solutions.
RESPONSIBILITIES:
- Design and develop AI-powered features using the Spring AI framework to interact with LLMs.
- Implement AI orchestration workflows using Spring AI components (ChatClient EmbeddingClient VectorStore).
- Build and maintain RAG (Retrieval-Augmented Generation) solutions for secure access to proprietary data.
- Integrate backend services with AI providers such as OpenAI Azure AI Anthropic etc.
- Manage and optimize vector stores (Pinecone Weaviate pgvector) for semantic search and document retrieval.
- Build scalable RESTful APIs using Spring Boot 3.x for AI-driven workloads.
- Collaborate with product teams to refine prompts and manage prompt templates.
- Ensure secure production-grade implementation using Spring Security.
- Deploy AI-enabled microservices using Docker Kubernetes and CI/CD pipelines.
- Ensure performance scalability and reliability of AI-powered enterprise applications.
Qualifications :
Bachelors or masters degree in computer science Information Technology or a related field.
Remote Work :
No
Employment Type :
Full-time
REQUIREMENTS: 6 years of Java development experience (Java 17 preferred).Strong experience with Spring Boot 3.x Spring Data and Spring Security.Hands-on experience with the Spring AI project (ChatClient EmbeddingClient VectorStore).Strong understanding of LLM concepts: tokens temperature model archi...
REQUIREMENTS:
- 6 years of Java development experience (Java 17 preferred).
- Strong experience with Spring Boot 3.x Spring Data and Spring Security.
- Hands-on experience with the Spring AI project (ChatClient EmbeddingClient VectorStore).
- Strong understanding of LLM concepts: tokens temperature model architectures.
- Experience implementing RAG and working with vector databases.
- Experience with vector stores like Pinecone Weaviate pgvector etc.
- Experience with SQL/NoSQL databases and integrating them into enterprise apps.
- Familiarity with Docker Kubernetes and CI/CD pipelines.
- Experience integrating AI providers (OpenAI Azure AI Anthropic) into enterprise systems.
- Strong problem-solving and architectural skills for production-grade AI solutions.
RESPONSIBILITIES:
- Design and develop AI-powered features using the Spring AI framework to interact with LLMs.
- Implement AI orchestration workflows using Spring AI components (ChatClient EmbeddingClient VectorStore).
- Build and maintain RAG (Retrieval-Augmented Generation) solutions for secure access to proprietary data.
- Integrate backend services with AI providers such as OpenAI Azure AI Anthropic etc.
- Manage and optimize vector stores (Pinecone Weaviate pgvector) for semantic search and document retrieval.
- Build scalable RESTful APIs using Spring Boot 3.x for AI-driven workloads.
- Collaborate with product teams to refine prompts and manage prompt templates.
- Ensure secure production-grade implementation using Spring Security.
- Deploy AI-enabled microservices using Docker Kubernetes and CI/CD pipelines.
- Ensure performance scalability and reliability of AI-powered enterprise applications.
Qualifications :
Bachelors or masters degree in computer science Information Technology or a related field.
Remote Work :
No
Employment Type :
Full-time
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