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Sigma Software is seeking a Software Architect to lead MCP-based integration design, focusing on Node.js and AI orchestration within a FinTech context in Europe. You will shape scalable foundations, develop reusable platform components, and drive architecture standards across teams.
You will mentor engineers, ensure security and resilience, and collaborate with multiple product teams to align engineering practices with enterprise goals.
Are you passionate about architecture, scalable distributed systems, and emerging AI technologies? We are looking for a Software Architect with strong expertise in Node.js and AI integration technologies to help build scalable engineering foundations for enterprise-wide MCP adoption.
This role combines architecture leadership, platform engineering, and hands-on development focused on reusable MCP integrations, AI orchestration, and enterprise architecture standards. At Sigma Software, you will work on technically challenging products, collaborate with experienced engineering teams, and help shape scalable solutions for a modern European FinTech company.
Our Customer is one of Europe’s fastest-growing FinTech companies, delivering a comprehensive financial infrastructure platform for businesses. The company provides embedded financial services, including virtual cards, bank transfers, account management, and payment operations through scalable APIs and modern financial technology solutions. Operating in a high-scale and rapidly evolving environment, the Customer places strong emphasis on engineering excellence, platform scalability, and architectural consistency.
The project focuses on building the engineering foundation for enterprise-wide MCP adoption across multiple product teams. The initiative aims to establish shared architecture standards, reusable TypeScript/Node.js libraries, SDKs, templates, and development practices that enable scalable and consistent MCP-compatible integrations.
As a Software Architect, you will lead the design of scalable MCP-based integration solutions, establish engineering standards, and develop reusable platform components for AI orchestration, context management, authentication, and service integrations. You will also contribute to defining integration approaches and architecture best practices across multiple engineering teams.