AI Engineer Sênior

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Design, develop, and evolve AI agents and intelligent workflows using MCP-based architectures.
• Build RAG pipelines and context-retrieval mechanisms using vector databases and other retrieval technologies.
• Integrate AI agents with APIs, external tools, and services to support complex business workflows.
• Develop AI agents in Python, preferably using Google ADK.
• Build and maintain agentic workflows using DeepAgents.
• Integrate AI models and services through Vertex AI and Gemini models.
• Define technical architecture patterns, reusable components, and governance guidelines for AI platforms.
• Ensure strong observability across solutions through logging, metrics, tracing, and other monitoring practices.
• Collaborate with engineering and technical teams to ensure consistent integration between AI agents and enterprise applications.
• Design solutions aligned with business processes, integrations, technical requirements, and enterprise constraints.
• Ensure developed components are scalable, reusable, maintainable, and prepared for continuous evolution.
• Define and apply validation and evaluation strategies for LLMs and AI agents using metrics and approaches such as DeepEval and LLM-as-a-Judge.
• Contribute to the continuous improvement of AI engineering practices, frameworks, standards, and solution quality.

Requirements:

• Strong professional experience developing applications and solutions with Python.
• Hands-on experience building AI agents, intelligent workflows, and integrations with Generative AI models.
• Practical experience with DeepAgents.
• Strong understanding of MCP-based architectures and integrations.
• Experience implementing RAG pipelines and working with vector databases.
• Experience integrating APIs, tools, external services, and enterprise applications.
• Experience with Vertex AI and Gemini models.
• Ability to define technical standards, reusable abstractions, architecture patterns, and engineering best practices.
• Experience implementing observability practices, including logs, metrics, and distributed tracing.
• Knowledge of LLM and AI agent validation and evaluation, including tools such as DeepEval and LLM-as-a-Judge approaches.
• Strong collaboration skills and experience working with engineering, architecture, and technical squads.
• Systems thinking and the ability to understand data flows, integrations, dependencies, and constraints within complex enterprise environments.
• Experience with enterprise AI agent platforms is a plus.
• Experience defining technical governance for AI-based solutions is a plus.
• Knowledge of scalable architectures focused on component reuse is a plus.
• Experience working in complex corporate environments with multiple integrations and architectural constraints is a plus.
• Previous involvement in technical standardization initiatives or the evolution of internal frameworks is a plus.
• Knowledge of LLMOps, agent evaluation, and continuous AI solution operations is a plus.

Benefits:

• Meal and food allowance.
• Home office allowance.
• Medical insurance.
• Dental insurance.
• Life insurance.
• Birthday day off.
• TotalPass / Wellhub access.
• Boon Saúde app.
• Discount partnerships.
• Agreements with establishments and educational institutions.
• Welcome kit.
• Structured onboarding.
• Access to continuous learning and professional development programs.
• Dedicated learning initiatives.
• Employee well-being and support programs.
• Full-time remote work model.
• Inclusive work environment and support for professional development.