Microsoft Azure AI / Artificial Intelligence Architect / Lead

Technical Responsibilities

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Own the end-to-end design and rollout of AI solutions that accelerate sales forecasting, quote generation, and marketing content creation.
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Map current processes in Microsoft Dynamics 365 Business Central (BC); identify data sources, gaps, and integration points for AI.
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Architect and implement Azure-based services (Azure OpenAI Service, Cognitive Services, Azure Machine Learning, Data Factory, Synapse, Functions, Logic Apps) to ingest data, train models, and deploy scalable, secure APIs.
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Build and maintain reusable forecasting and CPQ models, prompt libraries, and generative-content templates; establish CI/CD and MLOps pipelines.
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Define and enforce AI governance: data quality standards, versioning, telemetry, bias mitigation, security, and Responsible AI compliance.
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Lead backlog grooming, sprint planning, and cross-functional collaboration with product, marketing, and IT; serve as the technical lead for adoption of AI across the organization
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Track and report performance metrics (latency, accuracy, ROI) and continuously optimize models and workflows.

Required Skills & Experience

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Successful track record of delivering data analytics / software solutions, with recent lead role(s) in production AI/ML and/or generative-AI deployments.
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Deep expertise in Azure AI stack (Azure OpenAI, Cognitive Services, Azure Machine Learning, Data Lake, Synapse, Data Factory) and in designing secure, high-availability cloud architectures.
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Hands-on knowledge of Microsoft Dynamics 365 Business Central APIs, AL extensions, and Power Platform (Power Automate, Power Apps, Copilot Studio, Dataverse).
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Strong programming background (Python, SQL) and proficiency with Git-based CI/CD, RESTful API design, and serverless/event-driven patterns.
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Proven delivery of forecasting, CPQ, or marketing-content AI solutions at enterprise scale; fluency in prompt engineering, retrieval-augmented generation, and vector databases (e.g., Azure Cosmos DB, Elastic).
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Experience standing up MLOps frameworks (MLflow, Azure ML pipelines) and monitoring for model drift, data shifts, and cost efficiency.
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Solid grasp of data governance, privacy (GDPR/CCPA), security best practices, and Responsible AI principles.
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Exceptional stakeholder-management and leadership skills; adept at evangelizing new technology and mentoring engineers in an agile environment.



This position is on-site in Dallas, specifically in the vicinity of Grapevine so candidates must be local, and willing to work onsite 5 days per week.