Senior AI Engineer

Posted 1ds ago

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Job Description

Engenheiro de IA Sênior desenvolvendo agentes, pipelines de RAG e integrações com Vertex AI para a consultoria digital Verity. Projetando soluções escaláveis e avaliando LLMs para aplicações corporativas.

Responsibilities:

  • 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 developed components are scalable, reusable, and ready for continuous evolution
  • Define and apply validation and evaluation strategies for LLMs and agents, using metrics and tools such as DeepEval and LLM-as-a-Judge approaches

Requirements:

  • 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
  • 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-level perspective for understanding data flows, integrations, and enterprise environment constraints