AI Automation Engineer

Firebird Tours, LLC; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Firebird Tours seeks an AI Automation Engineer to design, build, and deploy AI workflows using LLMs and low‑code platforms. You will own end‑to‑end AI automations across sales, finance, and back‑office functions.

You will translate business challenges into concrete AI solutions, integrate automations with internal tools and third‑party APIs, and ensure reliability through logging and error handling while controlling costs.

Qualifications

• Experience shipping production AI automations.
• Ability to translate business problems into AI solutions.
• Experience deploying AI agents or automations in production environments.

Responsibilities

• Design, build, and deploy AI workflows across sales, finance, and back-office functions.
• Integrate automations with internal tools and third-party APIs.
• Ensure reliability through logging, error handling, and cost control.
• Own AI automation workflows from definition to deployment and monitoring.

Skills

LLMs

n8n

Python

JavaScript/TypeScript

REST APIs

Webhooks

OAuth

Production AI automation

Tools

n8n

LLM APIs

Logging/Monitoring

Job description

Firebird Tours seeks an AI Automation Engineer to design, build, and deploy AI workflows using LLMs and low-code platforms. This role focuses on automating operational processes across sales, finance, and back-office functions. Ideal for engineers with hands‑on experience shipping production AI automations and a pragmatic approach to integrating new models.

This role involves end-to-end ownership of AI automation workflows, from problem definition to deployment and monitoring. You will translate vague business challenges from operational, sales, and finance teams into concrete AI solutions, leveraging LLMs and low-code platforms like n8n. The core responsibility is to integrate these automations with internal tools, CRMs, and third‑party APIs, ensuring reliability through robust logging, error handling, and cost control.

The technical stack centers on n8n, LLM APIs, and various integration protocols such as REST, webhooks, and OAuth. While the emphasis is on low‑code solutions, the ability to write Python or JavaScript/TypeScript for custom scripts or n8n nodes is essential for scenarios where low‑code platforms are insufficient. Success in this position requires a pragmatic approach to evaluating new models and tools, focusing on their practical utility in solving business problems.

Candidates should have demonstrable experience deploying AI agents or automations in production environments, not just theoretical knowledge. A strong understanding of modern LLMs, including prompting, tool/function calling, and retrieval techniques, is crucial. The role demands a product and operations mindset, enabling the engineer to scope business problems effectively and propose viable AI-driven solutions that deliver tangible value.