Technical Architect

Role Overview: As a Generative AI Technical Architect, you will be the principal technical authority responsible for designing, implementing, and governing enterprise-grade Generative AI (GenAI) solutions. Your role will involve utilizing deep technical expertise in large language models (LLMs) and enterprise system architecture to create secure, scalable, and ethically compliant GenAI applications that drive measurable organizational value. Key Responsibilities: - Define standards for deploying GenAI solutions, including Retrieval-Augmented Generation (RAG), autonomous agents, and model fine-tuning pipelines. - Develop Agentic AI applications for production scalable experience hands-on. - Conduct technology selection and evaluation, including foundational models (commercial and open-source), vector databases, and orchestration frameworks. - Design integration patterns to connect GenAI capabilities with core enterprise platforms and existing data infrastructure. - Architect technical solutions focusing on performance, cost optimization, and Responsible AI policies. - Ensure data security and privacy throughout the GenAI lifecycle, adhering to regulations such as GDPR. - Implement LLMOps practices for automated model deployment, monitoring, version control, and CI/CD pipelines. - Develop and maintain a forward-looking Generative AI technology roadmap, proposing strategic investments. - Act as the Generative AI Subject Matter Expert in engagements with C-level executives and business leaders. Qualifications Required: - Minimum of 10 years of experience in Technical Architecture, Data Architecture, or ML Engineering, with at least 3 years dedicated to architecting production-grade Generative AI. - Deep expertise with LLMs, Transformer architectures, Fine-Tuning/Transfer Learning, and techniques like RAG. - Proficiency with a major cloud provider (AWS, Azure, or GCP) and relevant AI/ML service offerings. - Mastery of Python, including data science and ML libraries like PyTorch and TensorFlow. - Proven experience in designing data pipelines for GenAI and integration with modern data architectures. - Strong understanding of containerization and MLOps tools for managing AI models. - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field. - Exceptional written and verbal communication skills, with the ability to present complex technical strategies. - Relevant certifications such as AWS/Azure/GCP Technical Architect Professional or specialized AI/ML certifications. Note: No additional details about the company were provided in the job description. Role Overview: As a Generative AI Technical Architect, you will be the principal technical authority responsible for designing, implementing, and governing enterprise-grade Generative AI (GenAI) solutions. Your role will involve utilizing deep technical expertise in large language models (LLMs) and enterprise system architecture to create secure, scalable, and ethically compliant GenAI applications that drive measurable organizational value. Key Responsibilities: - Define standards for deploying GenAI solutions, including Retrieval-Augmented Generation (RAG), autonomous agents, and model fine-tuning pipelines. - Develop Agentic AI applications for production scalable experience hands-on. - Conduct technology selection and evaluation, including foundational models (commercial and open-source), vector databases, and orchestration frameworks. - Design integration patterns to connect GenAI capabilities with core enterprise platforms and existing data infrastructure. - Architect technical solutions focusing on performance, cost optimization, and Responsible AI policies. - Ensure data security and privacy throughout the GenAI lifecycle, adhering to regulations such as GDPR. - Implement LLMOps practices for automated model deployment, monitoring, version control, and CI/CD pipelines. - Develop and maintain a forward-looking Generative AI technology roadmap, proposing strategic investments. - Act as the Generative AI Subject Matter Expert in engagements with C-level executives and business leaders. Qualifications Required: - Minimum of 10 years of experience in Technical Architecture, Data Architecture, or ML Engineering, with at least 3 years dedicated to architecting production-grade Generative AI. - Deep expertise with LLMs, Transformer architectures, Fine-Tuning/Transfer Learning, and techniques like RAG. - Proficiency with a major cloud provider (AWS, Azure, or GCP) and relevant AI/ML service offerings. - Mastery of Python, including data science and ML libraries like PyTorch and TensorFlow. - Proven experience in designing data pipelines for GenAI and integration with modern data architectures. - Strong understanding of containerization and MLOps tools for managing AI models. - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field. - Exceptional written and verbal communication skills, wit