• Desenvolver e evoluir soluções utilizando Inteligência Artificial Generativa e Large Language Models (LLMs). • Projetar e implementar agentes inteligentes e fluxos baseados em arquiteturas multiagentes. • Desenvolver APIs e serviços backend para integração de soluções de IA com sistemas corporativos. • Contribuir para definições arquiteturais, boas práticas de engenharia e evolução da plataforma de IA. • Atuar na implementação de soluções baseadas em RAG (Retrieval-Augmented Generation), Prompt Engineering e avaliação de modelos. • Promover qualidade, observabilidade, segurança e escalabilidade das soluções desenvolvidas. • Colaborar com times multidisciplinares e stakeholders na definição e evolução de soluções alinhadas às necessidades do negócio. • Apoiar tecnicamente o time na resolução de desafios complexos e na adoção de novas tecnologias relacionadas à IA.

• Lead cross-functional engineering and architecture teams in the end-to-end delivery of complex AI systems, ensuring technical excellence and delivery quality. • Define and enforce reference architectures, technical patterns, delivery standards, and accelerators for enterprise AI adoption (leveraging Azure capabilities where appropriate). • Provide senior-level architectural oversight on programs, guiding the design of advanced, distributed, AI-powered applications across multi-system enterprise environments. • Drive the integration of modern AI capabilities—such as generative AI, intelligent/agentic systems, and Model Context Protocol (MCP)—into production-ready software. • Champion best practices for performance, scalability, reliability, observability, and MLOps/LLMOps across all AI delivery engagements. • Serve as a trusted technical advisor to executive stakeholders (CIO, CTO, CDO), helping them define enterprise AI strategies and prioritize high-value opportunities. • Lead technical workshops, architecture reviews, and visioning sessions to align solution direction with business outcomes. • Represent 3Cloud’s technical leadership in client engagements, partner discussions, and industry events, effectively communicating complex AI and engineering concepts. • Oversee a portfolio of large-scale AI delivery programs, ensuring architectural integrity, risk mitigation, and alignment with client strategy. • Provide proactive technical guidance to remove delivery blockers, solve architectural challenges, and ensure teams are building scalable and secure solutions. • Mentor senior architects, tech leads, and engineers, raising the overall technical bar of the practice.

• Own the design and evolution of core capabilities within our internal AI agent platform to support high-impact business workflows and AI agents. • Define and improve deployment patterns, shared services, and orchestration approaches that enable complex agent use cases to run reliably. • Partner with business stakeholders to translate high-priority strategic goals into scalable AI agent solutions. • Work hands-on with builders to debug issues, answer technical questions, and unblock day-to-day development while also improving the underlying platform. • Investigate failing repositories, run code locally when needed, and fix infrastructure or environment issues at the root cause. • Build and maintain shared services—such as reusable modules, integration layers, logging patterns, and data access approaches—that multiple teams can leverage. • Drive decisions around observability, governance, permissions, reliability, and cost-aware usage to ensure our AI transformation is sustainable and secure. • Help set technical direction for how new capabilities should be designed so we create durable foundations rather than one-off solutions. • Collaborate across engineering and business functions to identify and shape new high-value opportunities for agent-led innovation.

• Lead and evangelize on best practices of capturing and retaining data • Create and leverage models, inferential statistics and prescriptive analysis to proactively solve business problems answering the questions “What will happen and what should we do about it?” • Often responsible for large, complex problems that have broad implications and are less frequent • Recommend solutions based on understanding of the context, connections, and conclusions • Reviews deliverables; proactively coaches others on approach and work product • Coordinate with data stewards and anticipate needs process/procedures • Make continuous improvements to data procedures, including data efficiency • Recommend best analysis method for the situation