AI Automation Engineer

About the role

We are seeking an AI Automation Engineer to design, build, and maintain intelligent automation solutions that blend workflow automation with modern large-language-model capabilities. In this hands-on role you will own end-to-end pipelines, turning manual processes into AI-powered tools that cut effort, reduce turnaround time, and improve accuracy across the business.

Key responsibilities

• Design and develop automation workflows that embed AI and LLM services into existing business and engineering processes.
• Build and deploy AI agents, prompt pipelines, and document-processing systems for parsing, extraction, classification and summarisation.
• Integrate third-party and internal APIs to connect data sources, applications and AI models into reliable end-to-end pipelines.
• Automate repetitive tasks using scripting, RPA, and low-code/no-code platforms where appropriate.
• Optimise prompts, model selection and pipeline logic for cost, latency and output quality.
• Monitor deployed automations, handle errors and edge cases, and maintain performance over time.
• Collaborate with business and technical stakeholders to identify automation opportunities and translate them into working solutions.
• Document architecture, workflows and handover material to ensure maintainability and scalability.

Required profile

• Bachelor’s degree in Computer Science, Software Engineering or a related field.
• 3–5 years of experience in software development, automation engineering or a similar build role.
• Strong programming skills in Python (or a comparable language) for automation and integration work.
• Hands-on experience integrating LLM APIs such as OpenAI, Anthropic or Azure OpenAI.
• Solid understanding of REST APIs, webhooks and data formats like JSON and XML.

Required skills

• Python
• OpenAI, Anthropic or Azure OpenAI APIs
• REST API integration
• JSON and XML
• Prompt engineering
• Azure cloud platform
• Low-code / no-code automation tools (Power Platform, Zapier, n8n, Make)
• RPA tools and process automation frameworks
• Document processing (PDF, DOCX, OCR) and large-scale data extraction
• Vector databases, embeddings and Retrieval-Augmented Generation (RAG)
• CI/CD pipelines, Git version control
• Docker containerisation