Artificial Intelligence Engineer | R664

Job Summary:

We are seeking a highly skilled and innovative Azure AI Engineer with hands-on experience designing and deploying scalable AI solutions using Microsoft Azure services. The ideal candidate will have a strong background in Azure AI Search, Azure Functions, Vector Databases, and advanced orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel. Prior experience or interest in emerging agent-based architectures such as Crew AI or similar agent frameworks is a strong plus.

Key Responsibilities:

- Design, develop, and deploy AI-powered applications using Azure services and modern orchestration tools.
- Build and maintain AI search experiences using Azure AI Search (formerly Cognitive Search) and integrate with vector-based retrieval systems.
- Implement serverless compute logic using Azure Functions for scalable and event-driven AI workflows.
- Work with Vector Databases (e.g., Azure Cosmos DB for vector search, Pinecone, Weaviate) to enable hybrid search and semantic retrieval.
- Utilize LangChain, LangGraph, or Semantic Kernel to build intelligent agent workflows, autonomous pipelines, and knowledge-based AI systems.
- Integrate and experiment with Crew AI-like multi-agent coordination and reasoning systems to simulate advanced AI behaviors.
- Collaborate closely with Data Scientists, Product Managers, and Software Engineers to turn prototypes into production-ready applications.
- Maintain a strong focus on performance, reliability, and security in cloud-deployed AI systems.
- Stay current on advancements in AI, LLM orchestration, vector search, and cloud-native machine learning tools.

Required Qualifications:

- 5+ years of experience working with Microsoft Azure services, especially within the AI and Cognitive stack.
- Hands-on experience with Azure AI Search, Azure Functions, and Azure OpenAI Service.
- Proficiency in Python or Node.js, with experience integrating AI wrappers like LangChain, LangGraph, or Semantic Kernel.
- Strong understanding of Vector Databases and their role in semantic search and RAG (Retrieval Augmented Generation) pipelines.
- Experience building LLM-powered applications using structured frameworks and agents.
- Solid understanding of modern MLOps, DevOps practices, and cloud-native architectures.
- Strong problem-solving skills and ability to work in an agile, fast-paced environment.