AI Automation Engineer

Responsibilities.

• Design, build, and maintain automated workflows using tools like n8n, Make, Zapier, and similar platforms.  

• Integrate third-party applications using APIs to optimize and automate internal processes across departments.  

• Develop custom scripts and logic using Python or similar languages to support more complex workflows.  

• Leverage LLMs (like OpenAI/GPT) to power business use cases; apply prompt engineering best practices for optimal model performance.  

• Collaborate cross-functionally to identify automation opportunities and translate them into efficient solutions.  

• Implement scalable, secure, and reliable CI/CD pipelines for deploying automation scripts and services.  

• Support containerized deployments (Docker, Kubernetes) where needed.  

• Stay up to date with new AI tools, automation platforms, and APIs that can improve efficiency and innovation.  

Requirements. Must-Have

• Strong experience with workflow automation platforms like n8n, Make, or Zapier. • Solid Python scripting experience (or similar programming language).  

• Good understanding of APIs—authentication, data formats, integration patterns. • Familiarity with LLM models and how to apply prompt engineering for real-world applications.  

• Demonstrated ability to learn new tools quickly and apply creative thinking to problem-solving.  

• Excellent logical reasoning and aptitude—able to dissect complex systems and build simplified, automated versions.  

Nice-to-Have:

• Experience with containerization tools like Docker or Kubernetes.  

• Exposure to CI/CD pipelines and version control (Git).  

• Background in DevOps or systems integration.  

• Familiarity with data pipelines, webhooks, or serverless frameworks.