
Ai Engineer – Azure Ai
4 weeks ago
The ideal candidate will have hands-on experience building Retrieval-Augmented Generation (RAG) applications and intelligent agents, integrating services like Azure Open AI, Cognitive Search, Speech, and Document Intelligence.
In addition to solution design, you will be responsible for writing clean, efficient Python backend code to operationalize these systems.
Key Responsibilities:Design and develop scalable AI solutions using Azure AI services, including:Azure Open AIAzure Cognitive SearchAzure Speech Services (speech-to-text, text-to-speech)Azure Document Intelligence (formerly Form Recognizer)Architect and implement RAG-based applications and intelligent agents for search, document processing, and other NLP/NLU use cases.Write robust, maintainable Python backend code to integrate and orchestrate Azure AI services.Optimize performance, cost, and scalability of deployed AI workloads.Develop APIs and service layers to enable AI features across products and platforms.Collaborate with data scientists, Dev Ops, and product teams to deploy AI models and pipelines.Monitor, troubleshoot, and maintain AI-driven features in production environments.Stay current with Azure's evolving AI stack and emerging best practices in RAG and Gen AI.
Required Skills & Qualifications:Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, or a related field.7+ years of experience in AI/ML or backend software engineering.Strong hands-on experience with Microsoft Azure AI services.Proven experience in building and deploying RAG (Retrieval-Augmented Generation) applications.Proficient in Python, including building RESTful APIs, microservices, and data processing pipelines.Familiarity with vector databases, embedding models, and semantic search.Experience with Azure AI SDKs, REST APIs, and security/authentication mechanisms.Strong understanding of NLP, LLMs, prompt engineering, and AI agent design.Excellent problem-solving, collaboration, and communication skills.
Preferred Qualifications:Experience integrating Azure AI services into enterprise workflows or internal tools.Knowledge of Lang Chain, Semantic Kernel, or similar LLM frameworks.Familiarity with CI/CD pipelines and infrastructure-as-code on Azure.Exposure to MLOps and model lifecycle management on Azure ML.Experience working in agile development environments.
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