Solutions
Recruitment Software
Post jobs, import profiles, add screening questions, and manage hiring all in one place with personalized questions and control the entire recruitment process.
Recruitment Service
Let our expert team handle the key stages of tech recruitment for you with our specialized team acting in the main stages of recruitment.
Talent Pool
Top-tier Brazilian tech professionals, pre-vetted and ready for action, all pre-selected and ready for new opportunities.
Our Plans
Discover the perfect plan for your needs.
Use Cases
Build my own team
Define the profile, validate with our experts, and assemble your tech team with full control over every step.
Autopilot
Put tech recruitment on autopilot and receive pre-vetted candidates matched to your needs without lifting a finger.
Complete Solution
From sourcing to hiring — an end-to-end tech recruitment experience powered by AI, specialists, and a curated talent pool.
Why Geekhunter?
Resources
HR Blog
Contents about people management, organizational culture and trends in human resources.
Glossary
A comprehensive guide to the key terms and concepts in tech recruitment and software development.
Frequently Asked Questions
Clear answers to the most common questions about using the platform and recruitment processes.
EN
Nava Technology for Business
São Paulo, SP, Brasil
Arquiteto de soluções GenAIOps
Remote
(Anywhere)
Salary Range
R$11,000.00 - R$13,000.00 / month
Experience Level
Senior
Requirements
Tasks and Responsibilities
Projetar, implementar e desenvolver de sistemas baseados em GenAIOps, implementando práticas de CI/CD e monitoramento de modelos;
Trabalhar com ferramentas como Vertex AI, GKE, Cloud Functions e Cloud Run, AgentSpace, AgentEngine e arquiteturas AI-multiagent.
Background em desenvolvimento de sistemas em Java / Python;
Experiência com produtos do Google Cloud Platform (GCP), especialmente GKE, Cloud Run, Cloud Functions e Vertex AI, ADK, AgentSpace, AgentEngine;
Conhecimento de práticas de CI/CD e ferramentas com o Github, Jenkins ou similares;
Conhecimento de protocolos A2A vs MCP, RAG (Retrieval-Augmented Generation). Responsible AI, LLMs e Frameworks de IA (ex LangChain, CrewAI)
Conhecimento em APIs REST e micro serviços;
Experiência com arquiteturas de dados modernas de IA Generativa;
Certificação em Google Cloud Platform (como Professional Machine Learning Engineer ou Data Engineer);
Familiaridade com MLOps, incluindo monitoramento, retraining e rastreamento de modelos;
Familiaridade no uso de frameworks e plataformas de versionamento de modelos e experimentos, como MLflow ou similares.
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