Design and build production-grade AI features and REST APIs using Spring AI and Spring Boot. Implement RAG and vector search, integrate LLM providers, manage vector stores, ensure security with Spring Security, and deploy scalable microservices with Docker, Kubernetes, and CI/CD.
Company Description
👋🏼We're Nagarro, we are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job DescriptionREQUIREMENTS:
- 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.
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Top Skills
Anthropic
Azure Ai
Chatclient
Ci/Cd
Docker
Embeddingclient
Java 17
Kubernetes
NoSQL
Openai
Pgvector
Pinecone
Rag
Restful Apis
Spring Ai
Spring Boot 3.X
Spring Data
Spring Security
SQL
Vectorstore
Weaviate
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