Enterprise Software Architect (EMEA)

We are looking for a highly skilled .NET Enterprise Software Architect to spearhead the technical vision and design of our enterprise AI-driven translation platform. You will help bring together many internally developed tools into a suite of products that meet complex language localisation requirements with robust, scalable, and high-performance software. In this role, you will lead technology teams, enforce architectural best practices, and integrate cutting-edge machine learning and Large Language Models (LLMs) into our core .NET ecosystem. Responsibilities Architecture & Design: Design scalable, distributed .NET systems optimized for processing massive volumes of multilingual textual and audio data. AI & LLM Integration: Architect secure API integrations and middleware connecting .NET workflows with translation models, LLMs, and custom NLP pipelines. Analyzing the existing tools used in Translation Management services and building a suite of products or a platform that could be customized for individual customer needs with minimal configuration and fine-tuning. Technology Leadership: Define technical standards, coding guidelines, and architectural blueprints tailored for AI-assisted localization pipelines. Mentorship: Provide guidance and technical mentoring to developers, conducting thorough design and code reviews to ensure quality deliverables. Qualifications Education, skills, and experience Bachelor’s degree in Computer Science, Software Engineering, or a related field. Minimum 10 to 12+ years in software development, with at least 3 years in a dedicated .NET architecture role. Hands-on System Design experience in building large, complex microservices-based solutions. Deep expertise in C#, .NET 8+, ASP.NET Core, Java, ReactJS and asynchronous programming patterns. Proven experience integrating AI frameworks, vector databases, or cognitive services (e.g., Azure OpenAI, Semantic Kernel) into .NET applications. Strong proponent of Agile process and industry-standard SDLC methodologies. Strong knowledge of cloud-native infrastructure (Azure/AWS), message brokers (RabbitMQ/Kafka), and managing large-scale dataset storage. Please check our Privacy Policy to find out more about who is administrator of your personal data after application, purposes and your rights.