REQUIREMENTS:
- Total experience: 7 years
- Strong expertise in Java development (Java 17 or higher preferred).
- Strong expertise in Spring Boot 3.x Spring Data and Spring Security.
- Hands-on experience with framework (ChatClient EmbeddingClient VectorStore abstractions).
- Proficiency in SQL Server and experience with SQL/NoSQL databases.
- Understanding of LLM concepts (tokens temperature model architectures).
- Experience integrating and managing vector stores (Pinecone Weaviate pgvector) for document retrieval and similarity searches.
- Familiarity with Docker Kubernetes and CI/CD pipelines for deploying AI-enabled microservices.
- Knowledge of Retrieval-Augmented Generation (RAG) patterns and secure data access.
- Ability to collaborate with product teams to refine prompts and manage prompt templates.
- Good understanding of emerging AI technologies and backend integration.
RESPONSIBILITIES:
- Design and develop AI-powered features using to interact with LLMs.
- Implement AI-orchestrated workflows and manage embeddings within enterprise applications.
- Build robust scalable RESTful APIs using Spring Boot for AI-driven workloads.
- Integrate backend services with AI providers (OpenAI Azure AI Anthropic etc.).
- Manage vector databases for efficient document retrieval and similarity searches.
- Collaborate with cross-functional teams to deliver AI-enabled solutions.
- Ensure high-quality deliverables scalability and adherence to timelines.
Qualifications :
Bachelors or masters degree in computer science Information Technology or a related field.
Remote Work :
Yes
Employment Type :
Full-time
REQUIREMENTS:Total experience: 7 yearsStrong expertise in Java development (Java 17 or higher preferred).Strong expertise in Spring Boot 3.x Spring Data and Spring Security.Hands-on experience with framework (ChatClient EmbeddingClient VectorStore abstractions).Proficiency in SQL Server and experie...
REQUIREMENTS:
- Total experience: 7 years
- Strong expertise in Java development (Java 17 or higher preferred).
- Strong expertise in Spring Boot 3.x Spring Data and Spring Security.
- Hands-on experience with framework (ChatClient EmbeddingClient VectorStore abstractions).
- Proficiency in SQL Server and experience with SQL/NoSQL databases.
- Understanding of LLM concepts (tokens temperature model architectures).
- Experience integrating and managing vector stores (Pinecone Weaviate pgvector) for document retrieval and similarity searches.
- Familiarity with Docker Kubernetes and CI/CD pipelines for deploying AI-enabled microservices.
- Knowledge of Retrieval-Augmented Generation (RAG) patterns and secure data access.
- Ability to collaborate with product teams to refine prompts and manage prompt templates.
- Good understanding of emerging AI technologies and backend integration.
RESPONSIBILITIES:
- Design and develop AI-powered features using to interact with LLMs.
- Implement AI-orchestrated workflows and manage embeddings within enterprise applications.
- Build robust scalable RESTful APIs using Spring Boot for AI-driven workloads.
- Integrate backend services with AI providers (OpenAI Azure AI Anthropic etc.).
- Manage vector databases for efficient document retrieval and similarity searches.
- Collaborate with cross-functional teams to deliver AI-enabled solutions.
- Ensure high-quality deliverables scalability and adherence to timelines.
Qualifications :
Bachelors or masters degree in computer science Information Technology or a related field.
Remote Work :
Yes
Employment Type :
Full-time
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