GenAI Engineer

As a GenAI Engineer, your role involves designing and implementing AI-enabled enterprise applications integrated with secure APIs and workflow engines. You will be responsible for the following key tasks: - Develop RAG-based AI systems - Integrate OpenAI/Azure OpenAI APIs - Secure AI endpoints using OAuth2 - Integrate AI services with Spring Boot and ActiveMQ - Optimize performance and token usage To qualify for this position, you should meet the following requirements: - 36 years of experience in AI/ML or backend development - Strong Python programming skills - Experience with LLM APIs (OpenAI/Azure) - Experience building chatbot or RAG systems - Understanding of API security The technical stack and environment you will be working with include: - Backend: REST APIs, Microservices - Security: Spring Security, OAuth2, JWT, RBAC - Databases: PostgreSQL, MySQL, MongoDB - DevOps: Docker, Kubernetes, CI/CD - Cloud: AWS / Azure - AI Stack: Python, FastAPI, LangChain, LlamaIndex, HuggingFace - Vector Databases: FAISS / Pinecone / Weaviate Please note that the company may have additional details that are not mentioned in the job description. As a GenAI Engineer, your role involves designing and implementing AI-enabled enterprise applications integrated with secure APIs and workflow engines. You will be responsible for the following key tasks: - Develop RAG-based AI systems - Integrate OpenAI/Azure OpenAI APIs - Secure AI endpoints using OAuth2 - Integrate AI services with Spring Boot and ActiveMQ - Optimize performance and token usage To qualify for this position, you should meet the following requirements: - 36 years of experience in AI/ML or backend development - Strong Python programming skills - Experience with LLM APIs (OpenAI/Azure) - Experience building chatbot or RAG systems - Understanding of API security The technical stack and environment you will be working with include: - Backend: REST APIs, Microservices - Security: Spring Security, OAuth2, JWT, RBAC - Databases: PostgreSQL, MySQL, MongoDB - DevOps: Docker, Kubernetes, CI/CD - Cloud: AWS / Azure - AI Stack: Python, FastAPI, LangChain, LlamaIndex, HuggingFace - Vector Databases: FAISS / Pinecone / Weaviate Please note that the company may have additional details that are not mentioned in the job description.