Artificial Intelligence Architect

About the role

Lead the definition, evolution, and adoption of the technological architecture that will underpin the organization's AI solutions: robust, scalable, secure, and sustainable architectures, establishing principles, patterns, and standards. Profile with a global technical vision and technological judgment, capable of evaluating alternatives, selecting technologies, and defining how to integrate AI solutions with corporate applications, data, services, and systems. Works especially with generative AI, LLMs, RAG, intelligent agents, and cloud technologies, from architecture definition to supervising its implementation, evolution, and scaling. Collaborates closely with development, data, and business teams to ensure technically sound, maintainable solutions that are ready to grow. We especially value the ability to analyze trends, evaluate new tools, and define strategies to leverage AI's potential in a secure, efficient, and sustainable long-term manner.

What you'll do

• Design technical architectures for generative AI, LLMs, RAG, and agents; select models, technologies, and platforms according to each project; design cloud architectures with a focus on Microsoft Azure and for development, testing, and production environments.
• Design the integration of AI solutions with applications, APIs, databases, and information sources; define architecture patterns and reusable components; establish technical standards and best practices.
• Incorporate security, privacy, traceability, scalability, and governance criteria from the design stage; provide technical support to development teams during the construction and evolution of solutions.
• Define strategies for the evaluation, monitoring, and evolution of models; analyze new technologies, models, tools, and platforms; drive PoCs to validate new approaches; maintain an updated vision of AI evolution.

What we're looking for

• Experience in the architecture, design, and/or development of AI solutions and cloud services; experience working with APIs, applications, and various information sources; experience in the optimization and cost control of cloud/AI services.
• Solid knowledge of AI, machine learning, and generative AI; language models, retrieval-augmented generation, vector representations, semantic search, and agents; software architecture and integration patterns; Microsoft Azure ecosystem applied to AI.
• Ability to transform functional and technical requirements into architectural designs; analyze alternatives and select the most suitable solution; define standards, patterns, and best practices.
• Analytical and problem-solving capacity with autonomy for complex problems; technical judgment and initiative to make technological decisions; ability to learn and adopt new technologies; proactive and versatile profile with a continuous interest in the evolution of AI.

Nice to have

• Postgraduate training or certifications in Artificial Intelligence, Machine Learning, Data Science, Cloud Computing (Azure), or Microsoft technologies will be valued.

Education & certifications

• Degree in Computer Engineering, Software Engineering, or Computer Science.
• Degree in Industrial Engineering (specialties in Industrial Organization, Industrial Electronics, Automation and Robotics, Mechanics, or Industrial Technologies).
• Degree in Telecommunications Engineering.
• Degree in Biomedical Engineering, Aerospace Engineering, or related technical degrees with a strong analytical and technological component.