Fullstack AI Engineer - Sênior

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 a Fullstack AI Engineer - Sênior based in Brazil.

Technical Tools

Machine Learning EngineerData

Join a forward-looking technology environment focused on turning AI opportunities into practical, high-impact solutions. You’ll build prototypes, automations, integrations, and MVPs that combine generative AI with modern web technologies. The role sits at the intersection of engineering, product, and business, giving you direct influence over how processes are transformed through technology. You’ll work with AI agents, copilots, intelligent workflows, APIs, internal systems, and automation platforms. The position offers significant autonomy to evaluate technical feasibility, experiment with emerging tools, and move promising concepts toward production. You’ll also help shape secure, scalable architectures while translating complex technical concepts for non-technical stakeholders. This is an excellent opportunity for a senior engineer who enjoys rapid experimentation, innovation, and delivering tangible business value.

Develop prototypes and functional MVPs using generative AI, automation, APIs, and modern web technologies.
Design and implement automated workflows using n8n and API-based integrations.
Leverage AI-assisted development tools such as Claude, Claude Code, Lovable, OpenAI, GitHub Copilot, and similar technologies to accelerate delivery.
Develop and evolve solutions using multiple programming languages and technologies, including Node.js, React, Python, and PHP.
Integrate internal systems, databases, web applications, APIs, and AI-powered tools into cohesive solutions.
Contribute to the technical design of AI agents, copilots, assistants, and intelligent workflows.
Assess technical feasibility, effort, risks, dependencies, and architecture options for proposed solutions.
Apply good practices around security, authentication, logging, data protection, and responsible use of AI-generated solutions.
Document prototypes and technical solutions while supporting the transition of successful MVPs toward production-ready implementations.
Analyze existing business processes (As-is) and collaboratively design improved future-state processes (To-be) focused on measurable value and efficiency.
Partner closely with product, business, and technology stakeholders to identify opportunities and translate them into practical technical solutions.

Requirements

~2 min read

5+ years of professional software development experience.
Hands-on experience with AI-assisted software development, including tools such as Claude Code, Lovable, GitHub Copilot, or similar AI/vibe-coding platforms.
Proven experience designing or developing AI Agents and intelligent workflows.
Strong ability to understand business needs, evaluate existing processes, and propose future-state solutions that generate measurable value.
Practical experience with n8n for workflow automation and system integrations.
Demonstrated ability to rapidly develop prototypes and evolve successful concepts into functional MVPs.
Strong knowledge of Node.js, React, and REST API integration.
Practical Python experience for automation, scripting, data processing, or AI integrations.
Familiarity with PHP and the ability to work across multiple technology stacks.
Familiarity with LangChain, LangGraph, or comparable AI/agent development frameworks.
Understanding of cloud technologies, Docker, CI/CD, DevOps, or serverless architectures.
Solid knowledge of generative AI, LLMs, prompt engineering, and AI APIs.
Strong communication skills and the ability to collaborate effectively with product, business, and engineering teams.
High degree of autonomy, ownership, and delivery focus.
Ability to translate complex technical concepts into clear language for non-technical stakeholders.
Innovative mindset with the confidence to experiment and take calculated risks.
Nice to have: knowledge of RAG, embeddings, and vector databases.
Nice to have: knowledge of LGPD, data security, and AI governance.
Nice to have: familiarity with BMAD methodology and agent orchestration.
Nice to have: experience in education or healthcare environments.
Nice to have: familiarity with TOTVS/RM or Protheus.