AI Engineer – Azure AI & RAG Applications

AI Engineer

Key Responsibilities:

• Design and develop scalable AI solutions using

  Azure AI services

  , including:
• Azure OpenAI
• Azure Cognitive Search
• Azure 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, DevOps, 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 GenAI.

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

  LangChain

  ,

  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.