• Diagnose business problems before building solutions • Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration • Design, develop, and ship AI-powered solutions quickly • Improve organizational flow by building solutions that reduce bottlenecks • Integrate AI capabilities into existing systems and workflows • Partner closely with stakeholders across functions • Define and track success through business metrics and feedback loops

• Build AI applications: chatbots, knowledge assistants, and copilots • Implement multi-LLM orchestration across Azure OpenAI, OpenAI, and other providers • Work with data engineers to leverage datasets for RAG workflows • Integrate AI solutions into business processes using Power Platform • Deploy AI apps on Azure (Functions, App Services, AKS, VMs) • Implement CI/CD and MLOps pipelines using Azure DevOps or GitHub Actions • Monitor performance, reliability, and cost using Azure Monitor and Application Insights • Maintain technical documentation and reusable assets • Stay current with Azure AI, Copilot, and related technologies

• Design, build, and deploy AI-powered applications on Azure • Work with Azure AI Services, Azure OpenAI, Copilot Studio, Power Platform, and multi-LLM orchestration to deliver chatbots, knowledge assistants, and enterprise copilots • Collaborate with data engineers and business teams to create production-ready AI solutions that are scalable, secure, and impactful • Build AI applications: chatbots, knowledge assistants, and copilots • Implement multi-LLM orchestration across Azure OpenAI, OpenAI, and other providers • Work with data engineers to leverage datasets for RAG workflows • Integrate AI solutions into business processes using Power Platform • Deploy AI apps on Azure (Functions, App Services, AKS, VMs) • Implement CI/CD and MLOps pipelines using Azure DevOps or GitHub Actions • Monitor performance, reliability, and cost using Azure Monitor and Application Insights • Maintain technical documentation and reusable assets • Stay current with Azure AI, Copilot, and related technologies

Role Description We are looking for an engineer with practical AI/LLM experience who can build production features in Ruby on Rails. This role is for someone who has worked with AI tools, LLM APIs, prompts, retrieval/context patterns, or AI-assisted workflows - and who also has the engineering depth to turn those ideas into reliable, tested, maintainable software. - Designing and building AI/LLM-assisted product features - Integrating LLM APIs into Ruby on Rails systems - Combining AI approaches with business logic, tests, fallbacks, and production safeguards - Owning features from technical design to production - Improving reliability, accuracy, consistency, latency, cost, security, and maintainability - Writing and maintaining automated tests, including unit, integration, and E2E tests - Debugging production issues and improving system behavior over time Qualifications - Practical experience building with AI/LLM technologies, not just using AI tools casually - Strong Ruby on Rails experience, ideally at a senior level - Good judgment about when AI is useful and when simpler engineering is better - Strong backend skills, including databases, API design, performance, background jobs, and security - Ability to break down ambiguous problems into clear technical solutions Requirements - CI/CD, background jobs, or AWS experience (nice to have) - Experience with text-processing, localization, translation, or multilingual products (nice to have) Benefits - Stable & self-funded: Founded in 2007, profitable, and independent. - Industry leaders: Creators of WPML, the #1 multilingual plugin for WordPress, used on 1.5M+ sites - Fully remote, async-friendly: Work from anywhere within EMEA hours - Engineering-driven culture: Ownership, autonomy, testing, and thoughtful problem-solving - Fair compensation and great benefits: Designed to support your well-being both inside and outside of work.