Artificial Intelligence/Generative AI Engineer

AI Solutions :

• Compulsory knowledge of AI Solutions like LLM usage, Agentic frameworks, RAG, MCP, etc.

Data Handling :

• Should know how to handle data in databases and graphs, such as Azure Databases, Azure Cosmos Graph DB, etc.

Python Proficiency :

• Should have high coding proficiency in Python.

Application Deployment :

• Must have good application deployment knowledge.

• Should have experience with taking applications from scratch to production.

Optimization Techniques :

• Must know optimization techniques to improve deployment capabilities, like reducing latency, reducing computation resources, etc.

Azure Tools :

• Should know usage of Azure AI Tools and other Azure features.

Key Responsibilities :

• Architect and implement robust RAG (Retrieval-Augmented Generation) pipelines to improve the accuracy and context-awareness of generative models for end-users.

• Integrate Model Context Protocol (MCP) standards to streamline data exchange and enhance interoperability across our AI service ecosystem.

• Develop and optimize high-performance Python-based applications that interface seamlessly with large-scale data infrastructures.

• Manage and scale data storage solutions using Cosmos DB, ensuring low-latency access and high availability for AI-driven features.

• Deploy and monitor AI models within the Azure AI ecosystem to ensure reliability, security, and cost-efficiency for our global client base.

• Collaborate with engineering leads to refine model performance and iterate on features based on real-time user feedback and system metrics.