Senior Data & AI Engineer – AI Agent

Posted Aug 21

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create and enhance intricate, specialized AI agents for various strategic phases of data utilization, from initial specification to final exposure.

• Architect orchestration frameworks among multiple specialized agents, ensuring efficient transitions, shared context, and consistency throughout the pipeline.

• Spearhead the integration of agents into corporate ecosystems and data platforms utilizing the MCP protocol and advanced APIs.

• Work collaboratively with cross-functional teams in Data Engineering, MLOps, and Governance to guarantee the implementation of guardrails and compliance with PII/PCI regulations.

• Define the technical distinctions between “skills” and “agents” within the ecosystem and guide the formulation of Architecture Decision Records (ADRs).

• Execute observability strategies, log monitoring, and quality control measures for agent behavior in production environments.

• Convert complex business needs and challenges into actionable architectures and structured specifications for AI agents.


⛳️ Requirements

• Advanced expertise and demonstrated experience in Python for data-centric applications and API-driven architectures.

• Senior-level experience in Data Engineering, encompassing distributed pipelines, ETL/ELT architectures, governance, and cataloging.

• Strong hands-on experience with Large Language Models (LLMs), advanced prompt engineering, and techniques for evaluating responses.

• Proficient in the MCP (Model Context Protocol) or significant experience in rapidly learning and applying new integration protocols.

• Experience in integrating services and corporate APIs within complex environments.

• Established familiarity with Git/GitHub, CI/CD pipelines, and best practices in software engineering.

• Proficient in English for reading and writing technical documentation and utilizing 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 comparable cloud solutions.

• Differentials: in-depth knowledge of MLOps (MLflow), Data Mesh architecture, and observability for Generative AI.

• Differentials: previous participation in large-scale projects within 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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