Enterprise AI/Generative AI Engineer (Azure OpenAI & Microsoft Copilot)
Focus Areas: Azure OpenAI MS Copilot Studio Python Power Platform AI/ML Implementation
Detail
Specification
Role
Enterprise AI Engineer
Location
Redmond WA (Remote)
Job Type
Contract Engagement
Duration
Long-Term
Domain
High-Technology Sector
Position Summary
We are seeking an experienced Enterprise AI Engineer to drive the design and implementation of next-generation Generative AI solutions aimed at enhancing core business operations within a major high-technology client. This role is highly focused on developing and deploying robust AI models building complex Copilot extensions and integrating intelligent systems seamlessly with critical enterprise platforms.
The ideal candidate possesses deep technical expertise in AI/ML engineering a strong command of Python and TypeScript and proven hands-on experience with the Microsoft Power Platform and Copilot Studio for creating agentic and operational AI workflows. This position requires a builder who can translate business needs into scalable compliant and impactful AI automation solutions.
Key Responsibilities
- Develop and Deploy production-ready Generative AI models for core operational workflows including anomaly detection financial forecasting and data reconciliation.
- Design and Build custom Copilot extensions and integrations to drive user productivity and automation across enterprise systems.
- Collaborate with Data Science IT and business teams to proactively identify and prioritize opportunities for AI-driven optimization and process improvement.
- Integrate AI solutions with enterprise platforms such as ERP systems reporting tools and data warehouses ensuring strict adherence to organizational security compliance and governance standards.
- Contribute to the establishment of best practices for prompt engineering and AI automation pipelines.
Required Qualifications
- Bachelors or Masters degree in Computer Science Data Science Engineering or a related technical field.
- Proven demonstrable experience in creating agentic AI workflows preferably integrated with Microsoft Copilot Studio and the Microsoft Power Platform.
- Deep expertise in operational workflows including complex forecasting and data reconciliation processes.
- Expert proficiency in primary development languages: Python and JavaScript/TypeScript.
- Strong understanding of API design RESTful services and middleware integration principles.
- Proficiency with AI/ML frameworks including Azure AI and OpenAI.
- Excellent analytical communication and complex problem-solving skills.
Preferred Qualifications
- Experience with advanced Microsoft enterprise tools such as Microsoft 365 Copilot Dynamics 365 Finance or Power BI.
- Familiarity with Robotic Process Automation (RPA) tools and large-scale enterprise data platforms.
- Fundamental understanding of core machine learning algorithms and deep learning architectures.
- Knowledge of prompt engineering methodologies and sophisticated AI automation pipelines.
Enterprise AI/Generative AI Engineer (Azure OpenAI & Microsoft Copilot) Focus Areas: Azure OpenAI MS Copilot Studio Python Power Platform AI/ML Implementation Detail Specification Role Enterprise AI Engineer Location Redmond WA (Remote) Job Type Contract Engagement Duration Long-Term Domain High-Tec...
Enterprise AI/Generative AI Engineer (Azure OpenAI & Microsoft Copilot)
Focus Areas: Azure OpenAI MS Copilot Studio Python Power Platform AI/ML Implementation
Detail
Specification
Role
Enterprise AI Engineer
Location
Redmond WA (Remote)
Job Type
Contract Engagement
Duration
Long-Term
Domain
High-Technology Sector
Position Summary
We are seeking an experienced Enterprise AI Engineer to drive the design and implementation of next-generation Generative AI solutions aimed at enhancing core business operations within a major high-technology client. This role is highly focused on developing and deploying robust AI models building complex Copilot extensions and integrating intelligent systems seamlessly with critical enterprise platforms.
The ideal candidate possesses deep technical expertise in AI/ML engineering a strong command of Python and TypeScript and proven hands-on experience with the Microsoft Power Platform and Copilot Studio for creating agentic and operational AI workflows. This position requires a builder who can translate business needs into scalable compliant and impactful AI automation solutions.
Key Responsibilities
- Develop and Deploy production-ready Generative AI models for core operational workflows including anomaly detection financial forecasting and data reconciliation.
- Design and Build custom Copilot extensions and integrations to drive user productivity and automation across enterprise systems.
- Collaborate with Data Science IT and business teams to proactively identify and prioritize opportunities for AI-driven optimization and process improvement.
- Integrate AI solutions with enterprise platforms such as ERP systems reporting tools and data warehouses ensuring strict adherence to organizational security compliance and governance standards.
- Contribute to the establishment of best practices for prompt engineering and AI automation pipelines.
Required Qualifications
- Bachelors or Masters degree in Computer Science Data Science Engineering or a related technical field.
- Proven demonstrable experience in creating agentic AI workflows preferably integrated with Microsoft Copilot Studio and the Microsoft Power Platform.
- Deep expertise in operational workflows including complex forecasting and data reconciliation processes.
- Expert proficiency in primary development languages: Python and JavaScript/TypeScript.
- Strong understanding of API design RESTful services and middleware integration principles.
- Proficiency with AI/ML frameworks including Azure AI and OpenAI.
- Excellent analytical communication and complex problem-solving skills.
Preferred Qualifications
- Experience with advanced Microsoft enterprise tools such as Microsoft 365 Copilot Dynamics 365 Finance or Power BI.
- Familiarity with Robotic Process Automation (RPA) tools and large-scale enterprise data platforms.
- Fundamental understanding of core machine learning algorithms and deep learning architectures.
- Knowledge of prompt engineering methodologies and sophisticated AI automation pipelines.
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