Dadoteca

Architect

• Support the design and implementation of solution architectures based on Artificial Intelligence and Generative AI.
• Gather and translate business requirements into technical solutions using AI, automation and data analysis.
• Develop and implement solutions using LLMs, RAG (Retrieval-Augmented Generation), AI agents and integrations with enterprise systems.
• Build and expose AI models and services via APIs and microservices.
• Implement solutions on cloud AI platforms, ensuring performance, security and governance.
• Participate in the definition and implementation of data architectures for AI applications, including Data Lakes, Data Warehouses and vector databases.
• Support proofs of concept (PoCs), technical testing and evaluation of new technologies.
• Apply best practices in development, governance, security and responsible use of Artificial Intelligence.
• Collaborate with multidisciplinary data, development and business teams to ensure proper integration of solutions.
• Support monitoring, maintenance and continuous evolution of deployed solutions using MLOps practices.
• Produce technical documentation, architecture diagrams and functional and technical specifications.
• Participate in technical meetings with clients and stakeholders to understand requirements and present solutions.

AI Architect – Mid-level

Public Relations

• Serve as the technical focal point during pre-sales phases for Data, Analytics, Power Platform, Automation, and Artificial Intelligence solutions.
• Participate in discovery meetings and requirements gathering with clients.
• Translate business needs into scalable technical solutions tailored to the client context.
• Design architectures involving modern data platforms, analytics, AI, and cloud computing.
• Support the development of MVPs, PoCs, and data platform modernization roadmaps.
• Prepare technical proposals, executive presentations, and project scopes.
• Support commercial proposals by defining assumptions, risks, dependencies, and success criteria.
• Perform effort estimations, technical sizing, and team definition for project implementation.
• Lead technical discussions with IT, data, business, architecture teams, and executives.
• Support the sales team in strategic negotiations and technical alignment with clients.
• Contribute to the evolution of the company’s Data & AI offerings and solution portfolio.
• Deliver technical and executive presentations to clients and stakeholders.
• Keep up with market trends and new technologies related to Data, Analytics, AI, and Cloud.

Pre-Sales Architect – Data, Analytics & AI

Business Analyst

• Conduct investigative analyses using multiple data sources
• Support the structuring of metrics, reports, and dashboards
• Work with large volumes of data, organizing information logically
• Identify information gaps and propose ways to obtain, test, or validate data
• Support multidisciplinary teams in critically reviewing scenarios and tracking decisions
• Contribute to continuous improvement of processes
• Translate technical analyses into clear communications

AI Architect – Mid-level

Pre-Sales Architect – Data, Analytics & AI

Senior Business Analyst