Qualifications
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We are seeking a highly skilled Sr
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Bachelor's degree in a related discipline and 8+ years' experience in a related field, or a Master's degree and 6+ years' experience, or a Ph.D. and 3+ years' experience, or 12 years' experience in lieu of a degree in a related field
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Proven experience as a Sr
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Lead AI Engineer with a focus on AI platform/solution support and generative AI
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Strong knowledge of Microsoft Azure, Microsoft Fabric, Azure AI Foundry, and Copilot Studio
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Proficiency in programming languages such as Python, R, Java, or C#
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Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch)
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Experience with DevOps practices and tools for continuous integration and deployment
Responsibilities
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Lead AI Engineer with expertise in AI platform/solution support, generative use case & PoC development, generative & operational AI assessments, core generative platform development & support, AI evolving skillsets & learning paths, and AI governance & oversight
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AI Platform / Solution Support: Design, develop, and deploy AI solutions using Microsoft Azure, Microsoft Fabric, Azure AI Foundry, Copilot Studio, and Azure ML platforms; provide technical support and troubleshooting for AI platforms to ensure optimal performance and reliability; collaborate with Architecture, Engineering, and Data science teams to integrate AI models into existing systems
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Generative Use Case & PoC Development: Develop and implement generative AI use cases and proof-of-concept (PoC) projects; work with stakeholders to identify and prioritize generative AI opportunities; create and test generative AI models to demonstrate their feasibility and value
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Generative & Operational AI Assessments: Conduct assessments of generative and operational AI models to ensure their effectiveness and alignment with business goals; evaluate AI models for performance, accuracy, and scalability; provide recommendations for improving AI models based on assessment results
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Core Generative Platform Development & Support: Lead the development and support of core generative AI platforms; ensure the scalability, reliability, and security of generative AI platforms; implement best practices for generative AI platform development and maintenance
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Ai Evolving Skillsets & Learning Paths: Develop and implement learning paths for AI skill development within the organization; stay up-to-date with the latest advancements in AI technologies and methodologies; provide training and mentorship to team members to enhance their AI skillsets
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Ai Governance & Oversight: Establish and enforce AI governance frameworks and policies; ensure compliance with ethical guidelines and regulatory requirements for AI usage; monitor and report on AI governance metrics to ensure responsible AI practices
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Leadership & Organizational Development: Build and lead a high-performing team, fostering engagement, growth, and results-driven execution; perform related duties & responsibilities as assigned/requested
Full Description
About Cox Enterprises
Cox empowers employees to build a better future, with exciting investments and innovations across transportation, communications, cleantech, and healthcare.
Our family of businesses, including Cox Automotive and Cox Communications, is shaping the future for all.
Job Summary
We are seeking a highly skilled Sr. Lead AI Engineer with expertise in AI platform/solution support,generative use case & PoC development, generative & operational AI assessments, core generative platform development & support, AI evolving skillsets & learning paths, and AI governance & oversight.
Responsibilities
• AI Platform / Solution Support: Design, develop, and deploy AI solutions using Microsoft Azure, Microsoft Fabric, Azure AI Foundry, Copilot Studio, and Azure ML platforms; provide technical support and troubleshooting for AI platforms to ensure optimal performance and reliability; collaborate with Architecture, Engineering, and Data science teams to integrate AI models into existing systems.
• Generative Use Case & PoC Development: Develop and implement generative AI use cases and proof-of-concept (PoC) projects; work with stakeholders to identify and prioritize generative AI opportunities; create and test generative AI models to demonstrate their feasibility and value.
• Generative & Operational AI Assessments: Conduct assessments of generative and operational AI models to ensure their effectiveness and alignment with business goals; evaluate AI models for performance, accuracy, and scalability; provide recommendations for improving AI models based on assessment results.
• Core Generative Platform Development & Support: Lead the development and support of core generative AI platforms; ensure the scalability, reliability, and security of generative AI platforms; implement best practices for generative AI platform development and maintenance.
• Ai Evolving Skillsets & Learning Paths: Develop and implement learning paths for AI skill development within the organization; stay up-to-date with the latest advancements in AI technologies and methodologies; provide training and mentorship to team members to enhance their AI skillsets.
• Ai Governance & Oversight: Establish and enforce AI governance frameworks and policies; ensure compliance with ethical guidelines and regulatory requirements for AI usage; monitor and report on AI governance metrics to ensure responsible AI practices.
• Leadership & Organizational Development: Build and lead a high-performing team, fostering engagement, growth, and results-driven execution; perform related duties & responsibilities as assigned/requested.
Qualifications
• Bachelor's degree in a related discipline and 8+ years' experience in a related field, or a Master's degree and 6+ years' experience, or a Ph.D. and 3+ years' experience, or 12 years' experience in lieu of a degree in a related field.
• Proven experience as a Sr. Lead AI Engineer with a focus on AI platform/solution support and generative AI.
• Strong knowledge of Microsoft Azure, Microsoft Fabric, Azure AI Foundry, and Copilot Studio.
• Proficiency in programming languages such as Python, R, Java, or C#.
• Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch).
• Experience with DevOps practices and tools for continuous integration and deployment.

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