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@Orchard

Senior Azure Generative AI Engineer

Dallas, TX · On-site

$95/hr

Senior Azure Generative AI Engineer Dallas TX @Orchard LLC is seeking a Senior Azure Generative AI ... The anticipated range for a base salary for this role is between $95-115K. There may be some ...

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How much do generative ai salary jobs pay per year?

As of Sep 2, 2026, the average yearly pay for generative ai salary in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is the average salary for a generative AI professional?

The average salary for a professional working in Generative AI varies depending on experience, role, and location. In the United States, entry-level positions typically start around $120,000 per year, while experienced engineers and researchers can earn between $180,000 and $300,000 or more, especially at leading tech companies. Factors such as educational background, specialization in areas like natural language processing or computer vision, and industry demand can significantly influence compensation. Additionally, many roles offer bonuses, stock options, or other benefits that add to total compensation.

What are some common challenges faced by professionals working in generative AI roles?

Professionals in generative AI roles often encounter challenges such as staying current with rapidly evolving technologies and research, managing large and complex datasets, and ensuring that generated outputs are both ethical and high-quality. Additionally, effective collaboration with cross-functional teams—such as data scientists, software engineers, and product managers—is crucial to successfully integrate generative models into real-world applications. These roles require continuous learning and adaptability to address new technical and ethical considerations as the field progresses.

What are the key skills and qualifications needed to thrive as a generative AI engineer, and why are they important?

To thrive as a Generative AI Engineer, you need a strong background in machine learning, deep learning, and programming (especially Python), often supported by a degree in computer science or related fields. Familiarity with frameworks like TensorFlow, PyTorch, and experience using cloud computing platforms are typically required, along with knowledge of generative models such as GANs and transformers. Creative problem-solving, collaboration, and effective communication are key soft skills that set top performers apart in this role. These skills ensure engineers can design innovative AI models, work seamlessly in teams, and drive successful AI solutions from concept to deployment.

What is the difference between Generative Ai Salary vs Machine Learning Engineer Salary?

AspectGenerative Ai SalaryMachine Learning Engineer Salary
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI modelsDegree in Computer Science, Data Science, or related fields; programming skills
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, and other industries
Industry UsageDeveloping AI models like chatbots, image generatorsBuilding predictive models, data analysis, system deployment

Generative AI specialists focus on creating models that generate content, while Machine Learning Engineers develop algorithms for predictive analytics. Both roles require strong technical skills and often overlap in AI projects, but their core responsibilities differ. Salary ranges vary based on experience, location, and industry demand.

Is Generative AI a good career path?

Generative AI is a growing field with increasing demand for professionals skilled in machine learning, deep learning, and neural networks. Careers in this area often require knowledge of programming languages like Python and familiarity with AI frameworks such as TensorFlow or PyTorch. It offers opportunities in research, development, and deployment across various industries, making it a promising career choice for those interested in AI technology.
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Generative Ai Salary jobs near you
Infographic showing various Generative Ai Salary job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, and 7% Contract. Highlights an 66% In-person, 7% Hybrid, and 27% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Senior Azure Generative AI Engineer

@Orchard

Dallas, TX • On-site

$95/hr

Full-time

Re-posted 12 days ago

Job description

Senior Azure Generative AI Engineer

Dallas TX

@Orchard LLC is seeking a Senior Azure Generative AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions using Microsoft Azure. This role will focus on building scalable AI applications leveraging Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, Azure Cognitive Services, and modern data engineering practices. As the Senior Gen AI Engineer, you will work closely with business stakeholders, architects, and engineering teams to deliver AI-powered solutions for enterprise and banking use cases.
Your duties and responsibilities:

  • Design, develop, and deploy enterprise Generative AI solutions using Microsoft Azure AI services.
  • Build AI-powered applications utilizing Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, and Azure Cognitive Services.
  • Design and implement Retrieval Augmented Generation (RAG) solutions using Azure AI Search and vector databases.
  • Develop scalable data ingestion, transformation, and preprocessing pipelines to support AI model training and inference.
  • Fine-tune, evaluate, and optimize Large Language Models (LLMs) for enterprise-specific use cases.
  • Collaborate with solution architects, data engineers, and business stakeholders to define AI solution architectures and implementation strategies.
  • Integrate AI services into enterprise applications using REST APIs, Python, and Azure cloud services.
  • Implement MLOps and LLMOps best practices for model deployment, monitoring, governance, and lifecycle management.
  • Ensure AI solutions comply with enterprise security, responsible AI, and regulatory requirements, particularly within the banking and financial services domain.
  • Troubleshoot production AI solutions and continuously improve model accuracy, performance, scalability, and cost optimization.
  • Stay current with emerging Azure AI capabilities and recommend innovative approaches to improve business outcomes.

Required qualifications to be successful in this role:

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

Compensation: Compensation ranges are determined by several factors, including skill set, experience, licensure and certifications, and location. The anticipated range for a base salary for this role is between $95-115K. There may be some flexibility for exceptionally qualified individuals.

Established in 2010, @Orchard LLC has an exceptional reputation, providing staffing solutions to time-sensitive, talent-scarcity issues to deliver better talent management ROI.  Our specialty lies in the critical area of program talent acquisition and resource management, not in one narrow skillset, but across many areas of technical and functional delivery. To learn more about our other exciting opportunities, visit our Jobs Page at www.atOrchard.com.