Description

Define the overall AI strategy, architecture, and roadmap for the organization.Evaluate business use cases and identify opportunities for AI, Machine Learning (ML), Generative AI, and Intelligent Automation.Design end-to-end AI solutions, including data, model, application, and infrastructure architecture.Select appropriate AI/ML frameworks, platforms, tools, and cloud services.Design AI platforms using Azure OpenAI, Azure AI Services, AWS AI/ML services, Google Vertex AI, or other AI ecosystems.Define data architecture, data pipelines, feature stores, and data governance standards.Lead the integration of AI solutions with enterprise applications and business processes.Design and implement Retrieval-Augmented Generation (RAG) architectures for Generative AI solutions.Define AI security, privacy, compliance, and responsible AI standards.Establish MLOps and LLMOps practices for model deployment, monitoring, and governance.Ensure AI solutions meet requirements for scalability, reliability, performance, and cost optimization.Review AI models for bias, explainability, fairness, and ethical compliance.Guide teams on prompt engineering, fine-tuning, model selection, and evaluation strategies.Conduct architecture reviews and provide technical leadership to development teams.Collaborate with business stakeholders, architects, data scientists, engineers, and security teams.Create technical documentation, architecture diagrams, standards, and best practices.Monitor emerging AI technologies and recommend adoption strategies. Essential Skills: Define the overall AI strategy, architecture, and roadmap for the organization.Evaluate business use cases and identify opportunities for AI, Machine Learning (ML), Generative AI, and Intelligent Automation.Design end-to-end AI solutions, including data, model, application, and infrastructure architecture.Select appropriate AI/ML frameworks, platforms, tools, and cloud services.Design AI platforms using Azure OpenAI, Azure AI Services, AWS AI/ML services, Google Vertex AI, or other AI ecosystems.Define data architecture, data pipelines, feature stores, and data governance standards.Lead the integration of AI solutions with enterprise applications and business processes.Design and implement Retrieval-Augmented Generation (RAG) architectures for Generative AI solutions.Define AI security, privacy, compliance, and responsible AI standards.Establish MLOps and LLMOps practices for model deployment, monitoring, and governance.Ensure AI solutions meet requirements for scalability, reliability, performance, and cost optimization.Review AI models for bias, explainability, fairness, and ethical compliance.Guide teams on prompt engineering, fine-tuning, model selection, and evaluation strategies.Conduct architecture reviews and provide technical leadership to development teams.Collaborate with business stakeholders, architects, data scientists, engineers, and security teams.Create technical documentation, architecture diagrams, standards, and best practices.Monitor emerging AI technologies and recommend adoption strategies

Key Skills

Education

Any Gradute