AI Engineer

BrazilRemoteFull-timemid

Machine Learning EngineerData

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Engineer based in Brazil. This is a fully remote,

Technical Tools

Machine Learning EngineerData

This is a fully remote, hands-on engineering role focused on building AI-powered products and backend services for a modern SaaS platform.
You’ll work primarily with Agentic AI, LLMs, MCP servers, and multi-agent orchestration while contributing to reliable, production-ready systems.
The role combines Python and Java development with opportunities to influence architecture, scalability, observability, and maintainability.
You’ll work closely with engineering, product, and QA colleagues in a fast-moving environment where ownership and technical judgment are highly valued.
AI-assisted development is part of the everyday workflow, with tools such as Cursor, Claude Code, and GitHub Copilot used to improve productivity and code quality.
You’ll have meaningful ownership over well-defined technical challenges and the opportunity to contribute to innovative AI applications at production scale.
This position is ideal for an independent engineer who enjoys learning, experimenting, and turning complex AI capabilities into practical products.

Design, develop, test, deploy, and support high-quality software across Agentic AI capabilities and backend services.
Build, operate, and consume MCP servers, including tool design, authentication and OAuth, multi-tenant security, and deployment.
Develop LLM agents using tool and function calling, as well as multi-agent orchestration approaches such as A2A or similar frameworks.
Test and evaluate agent behavior and implement appropriate observability for AI systems operating in production.
Build backend services primarily in Python for AI and agent workloads and Java for integration with the core platform, with attention to performance and data quality.
Contribute to architecture and technical design discussions, evaluating trade-offs related to scalability, reliability, and maintainability.
Use AI coding assistants such as Cursor, Claude Code, or GitHub Copilot as part of the development workflow.
Participate in code reviews and provide constructive feedback that improves code quality, consistency, and maintainability.
Identify technical debt and contribute practical solutions for addressing it.
Break complex development work into manageable tasks and deliver solutions reliably and independently.
Collaborate with Product Management and Quality Assurance to refine requirements and ensure deliverables meet high quality standards.
Share technical knowledge, new patterns, tools, and development practices with colleagues.
Contribute to frontend development when required, supporting occasional user-interface work.

Requirements

~2 min read

Be based in Brazil, Colombia, the Dominican Republic, or Mexico; this opportunity is open to candidates based in Brazil.
Strong written and spoken English, with the ability to work effectively in an entirely English-speaking environment.
4+ years of backend-focused software development experience using Java and Python, including substantial experience with Agentic AI.
Strong proficiency in Java and Python, including data structures, relational databases, and SQL.
Production experience building AI-driven applications, agentic products or features, and working with LLMs or frameworks such as LangChain or Google ADK.
Hands-on production experience building, operating, and consuming MCP servers, including tool design, authentication/OAuth, multi-tenant security, and deployment.
Experience building LLM agents with tool/function calling and multi-agent orchestration.
Experience testing and evaluating AI agent behavior and implementing production observability.
Practical experience using AI coding assistants such as Cursor, Claude Code, or GitHub Copilot in day-to-day development.
Experience with microservices and a solid understanding of backend architecture.
Familiarity with cloud platforms, particularly GCP, and infrastructure concepts such as containers, caching, and distributed systems is advantageous.
Strong attention to detail and commitment to unit and functional testing.
Ability to work independently, take ownership of well-defined problems, and drive them through to completion.
Strong communication, collaboration, problem-solving, and continuous-learning mindset.
Computer Science, Engineering, or another relevant technical background gained through formal education, practical experience, or a combination of both.
Experience with React and TypeScript, including familiarity with JavaScript design patterns and single-page applications, is a plus.