Senior Data & AI Engineer – AI Agent
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Job Description
Engenheiro de Dados e IA sênior desenvolvendo agentes multiagentes para consultoria brasileira de dados. Integrando LLMs, MCP, APIs e plataformas corporativas para o setor de pagamentos.
Responsibilities:
- Develop and evolve complex, specialized AI agents for strategic stages of the data harness, from specification through to exposure
- Design orchestration architectures among multiple specialized agents, ensuring performant handoffs, shared context and consistency across the pipeline
- Lead the integration of agents into corporate ecosystems and data platforms using the MCP protocol and advanced APIs
- Collaborate with multidisciplinary teams in Data Engineering, MLOps and Governance to ensure guardrails are applied and compliance with PII/PCI
- Define the technical boundary between “skills” and “agents” within the ecosystem and lead the creation of Architecture Decision Records (ADRs)
- Implement observability strategies, log monitoring and quality-control processes for agent behavior in production
- Translate complex business requirements and pain points into actionable architectures and structured specifications for AI agents
Requirements:
- Advanced mastery and proven experience in Python for data-oriented applications and API-based architectures
- Senior experience in Data Engineering, covering distributed pipelines, ETL/ELT architectures, governance and cataloging
- Solid hands-on experience with Large Language Models (LLMs), advanced prompt engineering and methods for evaluating responses
- Proficiency with the MCP (Model Context Protocol) or substantial experience in quickly learning and applying new integration protocols
- Experience integrating services and corporate APIs in high-complexity environments
- Established practice with Git/GitHub, CI/CD pipelines and software engineering best practices
- Fluent English for reading and writing technical documentation and using AI tools
- Differentials: advanced experience in multi-agent systems and orchestration frameworks such as LangChain, LangGraph, CrewAI or AutoGen
- Differentials: hands-on experience with the Databricks platform (Unity Catalog, Databricks Apps, Genie Spaces) or equivalent cloud solutions
- Differentials: deep knowledge of MLOps (MLflow), Data Mesh architecture and observability for Generative AI
- Differentials: prior involvement in large-scale projects in the financial or payments sector
Benefits:
- Hiring model can be PJ (independent contractor, no benefits) or CLT (formal employment with benefits)
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