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# Azure Generative AI Engineer

- **Company:** NALL & COMPANY, INC.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $69,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Python (Programming Language), Tensorflow, Azure Machine Learning, Search Technologies, Azure Data Factory, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Git, Microsoft Fabric, Containerization, Kubernetes, HuggingFace, Machine Learning Operations, Azure Synapse Analytics, Data Pipelines, Docker, Databricks
- **Published:** September 17, 2026
- **Apply:** https://www.thejobnetwork.com/job/d13d34f7-57b6-4b4f-8cd8-91d83521bb23/senior-azure-generative-ai-engineer-local-to-dallas-tx

## About the Role

* Minimum 6+ years of software engineering, data engineering, or AI/ML development experience.
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 * Minimum 3+ years of hands-on experience developing solutions on Microsoft Azure.
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 * Minimum 2+ years of hands-on experience building Generative AI or Large Language Model (LLM) applications.
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 * Experience delivering enterprise cloud solutions within regulated industries such as banking or financial services is highly preferred.
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Technical Skills\n
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 * Strong experience with Azure OpenAI Service.
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 * Hands on experience with Azure AI Foundry (formerly Azure AI Studio).
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 * Experience with Azure Machine Learning and Azure Cognitive Services.
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 * Strong understanding of Retrieval Augmented Generation (RAG) architecture.
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 * Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, or similar technologies.
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 * Strong Python programming skills.
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 * Experience with LangChain, LangGraph, Semantic Kernel, or similar GenAI orchestration frameworks.
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 * Experience with PyTorch, Hugging Face Transformers, or similar ML frameworks.
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 * Experience building scalable data pipelines using Azure Data Factory, Synapse, Microsoft Fabric, Databricks, or Spark.
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 * Understanding of prompt engineering, model evaluation, fine tuning, embeddings, and LLM optimization.
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 * Experience with CI/CD pipelines and MLOps/LLMOps practices.
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 * Familiarity with Git, Azure DevOps, and container technologies (Docker/Kubernetes) is preferred.
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 * Strong understanding of AI governance, responsible AI, and model security
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