AI Automation Engineer

Hyre · Mexico · posted today ago

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About this role

AI Automation Engineer

Work Type:Full-time.
Schedule:Standard US business hours.
Location:100% Remote.

Role Overview

We are seeking an innovative and skilled AI Automation Engineer who specializes primarily in building AI Agents and intelligent automation workflows. This role requires strong foundational expertise in AI development combined with solid coding capabilities to take on high-level technical challenges. You will be instrumental in bridging the gap between raw data and automated product features, utilizing tools like n8n, React, and TypeScript to bring AI concepts into production and drive real-world business solutions.

Key Responsibilities

AI Agent Development:Design, create, and deploy robust AI Agents tailored to specific business needs and automated workflows.
Workflow Automation:Utilize n8n to build, optimize, and manage complex automation pipelines that seamlessly integrate AI capabilities.
Full-Stack Integration:Leverage React and TypeScript to write clean, efficient code and integrate both custom-built AI models and third-party APIs (such as Large Language Models) into existing software applications.
Version Control & Collaboration:Manage codebases, track changes, and collaborate effectively with the engineering team using GitHub.
Deployment & Optimization:Deploy AI solutions into production environments, continuously monitoring performance and fine-tuning agents as necessary to maintain high accuracy and reliability.

Requirements & Qualifications

Experience: 3–5+ years of professional experience in software engineering, with a strong, proven focus on creating and developing AI Agents.
Technical Proficiency: Solid coding experience using React and TypeScript. Demonstrated knowledge of n8n and how to use it effectively for automation workflows.
Version Control: Familiarity and practical hands-on experience with version control using GitHub.
AI/ML Foundation: Experience with industry-standard machine learning libraries and deploying models on cloud platforms (e.g., AWS, Google Cloud, or Azure).
Core Competencies: Highly self-motivated with the ability to take a project from conceptualization to deployment, comfortably bridging mid-level execution and senior-level architectural decisions.
Remote Infrastructure: Must have a dedicated, noise-free home office setup equipped with a reliable, high-speed internet connection and a backup power source.

Preferred Qualifications (Bonus):

Familiarity with additional programming languages such as Python, C++, or Java is a strong plus.
Solid understanding of MLOps best practices and data pipeline optimization.