AI Engineer

Durapid Technologies Private Limited; Jaipur; On-site; INR 1,600,000 - 2,400,000; Full time

Job summary

Durapid Technologies Private Limited is seeking an AI Engineer Expert with 6–10 years of experience to design, develop, and deploy scalable AI/ML solutions. The role focuses on RAG, agentic systems, and integration with Azure cloud infrastructure.

You will work with LangChain/LangGraph, vector databases, and modern LLM frameworks to deliver autonomous, robust AI capabilities. The position demands hands-on experience with retrieval and deployment pipelines, strong collaboration with product and

Qualifications

• 6–10 years of AI/ML experience with production systems.
• Strong expertise in Retrieval-Augmented Generation (RAG) architectures.
• Hands-on with agentic AI systems and autonomous decision-making.
• Proficiency in cloud platforms, preferably Microsoft Azure.
• Experience with LangChain or LangGraph and modern LLM frameworks.
• Practical knowledge of vector databases and similarity search solutions.

Responsibilities

• Design, develop, and deploy scalable AI/ML models leveraging RAG and agentic systems.
• Integrate AI models with backend services and Azure infrastructure.
• Design and implement vector database solutions for efficient retrieval.
• Collaborate with product/engineering to translate business needs into AI solutions.
• Optimize prompts, fine-tuning, and evaluation pipelines for LLM apps.
• Ensure performance, reliability, and CI/CD integration for AI systems.
• Stay updated on AI/NLP/MLOps trends and share knowledge.

Skills

AI

RAG

Agentic

Azure

LangChain

LangGraph

Vector databases

Tools

Pinecone

Weaviate

Milvus

Azure Cognitive Search

Job description

Calling all AI Engineer Experts!

Experience: 6–10 Years

Notice Period: Immediate to 15 Days

Desired Expertise: AI | RAG | Agentic | Azure | LangGraph/LangChain | Vector Database

Role Responsibilities

• Design, develop, and deploy scalable AI/ML models and solutions leveraging RAG, Agentic systems, and modern LLM frameworks (e.g., LangChain, LangGraph).
• Integrate AI models with backend services and cloud infrastructure (preferably on Microsoft Azure).
• Design and implement vector database solutions (e.g., Pinecone, Weaviate, Milvus, Azure Cognitive Search) for efficient similarity search and retrieval.
• Collaborate with product and engineering teams to define AI use cases and translate business requirements into technical implementations.
• Optimize prompt engineering strategies, fine-tuning, and evaluation pipelines for LLM-based applications.
• Build and maintain agentic AI systems that perform autonomous decision-making and task execution.
• Ensure model performance, reliability, and scalability through rigorous testing, monitoring, and CI/CD integration.
• Stay current with the latest advancements in AI, NLP, and MLOps, and contribute to internal knowledge sharing.

Skills: vector, rag, database, langchain, azure