Senior AI Engineer

• Design, develop, and evolve agents and workflows using MCP-based architectures
• Build RAG pipelines and context-retrieval mechanisms using vector databases
• Integrate agents with APIs, tools, and external services to execute complex workflows
• Develop 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 architectural standards, reusable components, and technical governance guidelines for the platform
• Ensure solution observability through logs, metrics, and tracing
• Partner with technical teams to ensure consistent integration between AI agents and enterprise applications
• Design solutions aligned with business processes, integrations, and objectives
• Ensure that developed components are scalable, reusable, and prepared for continuous evolution
• Define and apply validation and evaluation strategies for LLMs and agents using metrics, DeepEval, and LLM-as-a-Judge

• Strong experience with Python development
• Hands-on experience building agents, intelligent workflows, and integrations with generative AI models
• Experience with DeepAgents
• Knowledge of MCP-based architectures
• Experience with RAG pipelines and vector databases
• Hands-on experience integrating APIs, tools, and external services
• Experience with Vertex AI and Gemini models
• Ability to define technical standards, reusable abstractions, and engineering best practices
• Experience with observability, including logs, metrics, and tracing
• Knowledge of LLM and agent validation and evaluation, including tools such as DeepEval and LLM-as-a-Judge approaches
• Ability to collaborate effectively with engineering, architecture, and technical squad teams
• Systems thinking to understand data flows, integrations, and enterprise environment constraints
• 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 in complex enterprise environments is a plus
• Previous involvement in technical standardization initiatives and the evolution of internal frameworks is a plus
• Knowledge of LLMOps practices, agent evaluation, and the continuous operation of AI solutions is a plus
• Experience with LLM and agent evaluation strategies and frameworks is a plus

• Meal voucher
• Food allowance
• Home office allowance
• Health insurance
• Dental insurance
• Life insurance
• Birthday day off
• Total Pass / Wellhub
• Boon Saúde app
• Discount partnerships
• Agreements with businesses and educational institutions
• Welcome kit
• Onboarding program
• Verity Learning
• Verity Break
• #VerityWithYou
• Access to professional development courses