Senior Gen AI Solutions Architect

As a Senior Gen AI Solutions Architect, your role involves designing, building, and scaling enterprise-grade AI applications using Azure OpenAI and cloud-native patterns. You will blend solution architecture with deep engineering expertise, focusing on RAG systems, AI agents, and enterprise integrations. Your responsibilities include architecting end-to-end Gen AI solutions, designing microservices and orchestration pipelines, leading integration with enterprise platforms, enforcing software architecture standards, guiding engineering teams, driving prompt engineering strategies, and overseeing deployment and lifecycle management of AI applications on Azure cloud platforms. Key Responsibilities: - Architect and implement end-to-end Gen AI solutions (RAG systems, AI agents) using Azure OpenAI and Azure services. - Design scalable microservices and orchestration pipelines for LLM workflows using Python and cloud-native principles. - Lead integration of AI systems with enterprise platforms such as SharePoint, Dynamics, Dataverse, and Microsoft Graph APIs. - Define and enforce software architecture standards using SOLID principles and proven design patterns. - Guide engineering teams (Leads, Senior Developers, Junior Developers) on best practices in AI development and cloud engineering. - Drive prompt engineering strategies and optimization for GPT-based and similar models in production scenarios. - Oversee deployment, monitoring, and lifecycle management of AI applications on Azure cloud platforms. Qualifications Required: - Must-Have Skills (all validated at 85% confidence): - Azure OpenAI + Azure AI Services (RAG & AI Agents) - .NET + Azure Cloud Application Development - Python for AI Microservices & LLM Workflows - Enterprise Integration (Graph API, SharePoint, Dynamics, Dataverse) - Design Patterns & SOLID Principles - Prompt Engineering & Agentic AI Design - Good-to-Have Skills: - Vector Databases (e.g., Azure Cognitive Search, Pinecone, etc.) - AI Solution Deployment & MLOps Practices on Azure - Architecture & Design Tools (Lucidchart, Visio, Draw.io) - Thought Leadership in Gen AI Use Cases If you need any additional details about the company or have any questions regarding the job description, feel free to ask. As a Senior Gen AI Solutions Architect, your role involves designing, building, and scaling enterprise-grade AI applications using Azure OpenAI and cloud-native patterns. You will blend solution architecture with deep engineering expertise, focusing on RAG systems, AI agents, and enterprise integrations. Your responsibilities include architecting end-to-end Gen AI solutions, designing microservices and orchestration pipelines, leading integration with enterprise platforms, enforcing software architecture standards, guiding engineering teams, driving prompt engineering strategies, and overseeing deployment and lifecycle management of AI applications on Azure cloud platforms. Key Responsibilities: - Architect and implement end-to-end Gen AI solutions (RAG systems, AI agents) using Azure OpenAI and Azure services. - Design scalable microservices and orchestration pipelines for LLM workflows using Python and cloud-native principles. - Lead integration of AI systems with enterprise platforms such as SharePoint, Dynamics, Dataverse, and Microsoft Graph APIs. - Define and enforce software architecture standards using SOLID principles and proven design patterns. - Guide engineering teams (Leads, Senior Developers, Junior Developers) on best practices in AI development and cloud engineering. - Drive prompt engineering strategies and optimization for GPT-based and similar models in production scenarios. - Oversee deployment, monitoring, and lifecycle management of AI applications on Azure cloud platforms. Qualifications Required: - Must-Have Skills (all validated at 85% confidence): - Azure OpenAI + Azure AI Services (RAG & AI Agents) - .NET + Azure Cloud Application Development - Python for AI Microservices & LLM Workflows - Enterprise Integration (Graph API, SharePoint, Dynamics, Dataverse) - Design Patterns & SOLID Principles - Prompt Engineering & Agentic AI Design - Good-to-Have Skills: - Vector Databases (e.g., Azure Cognitive Search, Pinecone, etc.) - AI Solution Deployment & MLOps Practices on Azure - Architecture & Design Tools (Lucidchart, Visio, Draw.io) - Thought Leadership in Gen AI Use Cases If you need any additional details about the company or have any questions regarding the job description, feel free to ask.