Job Opportunities API

Stanley/Stella is accelerating its digital transformation to strengthen customer experience and scale its business platforms across an international ecosystem of decorators, resellers, and partners. The Technology architect acts as the company’s  senior technical authority , reporting directly to the CIO. This role defines, governs, and continuously evolves the  technology foundations of the enterprise ensuring coherence, scalability, resilience, and security across all platforms, integrations, and data capabilities. This is a  cross-cutting technical mandate   not a functional management role  with accountability for integrating, securing, and anticipating technologies across the organization. The role prevents fragmentation, avoids short-term decisions with long-term consequences, and translates emerging technologies into  robust, production-ready foundations . A key and immediate priority is to lead the integration of AI technologies including RAG pipelines, agentic workflows, orchestration tools, low-code platforms, and API-based integrations  across the company’s core stack: Infor M3, HubSpot, Magento, Azure, and Power BI . “Build the AI foundations of today while helping define the engineering practices of tomorrow”  The Mission   Turn strategic technology and AI ambitions into operational reality. Design and operationalise a vendor-agnostic AI ecosystem, help define future engineering practices, and establish the architecture, standards, governance and platform capabilities that enable sustainable innovation across Stanley/Stella.   What You Will Build in the First 12 Months    Enterprise AI Reference Architecture and target AI Technology Stack  First production-ready Agent Platform   MCP standards and API-first integration patterns   AI Governance, Prompt Engineering, Evaluation and Drift Monitoring Frameworks  Enterprise AI Technology Radar  AI-Assisted Engineering Framework including vibe coding, application generation, testing, qualification and production readiness standards  As software engineering is being transformed by AI, low-code platforms and application-generation tools, you will help define how these capabilities should be safely adopted across the  organisation , including the guardrails, standards and best practices required to balance innovation, quality, security and maintainability.  AI & Engineering Adoption Dashboard measuring usage, maturity, compliance and value delivery   Your Impact   Build a model-agnostic AI architecture  Co-design AI-ready data foundations with the Data Lead  Drive MCP and API-first transformation  Define standards for agents, copilots, RAG and intelligent automation  Guide technology choices across AI platforms, cloud services, front-end frameworks, digital experience platforms and future engineering capabilities  Evaluate modern web technologies, composable architectures, React/Next.js ecosystems, AI-generated applications, low-code platforms and  industrialized   vibe coding approaches  Define the do’s and don’ts for AI-assisted development and application generation  Establish standards for automated testing, qualification, security reviews and production readiness Promote,  evangelize , measure and continuously improve the frameworks you define  Contribute to broader architecture, integration, observability, platform and security topics  Adoption, Governance & Measurement   You do not ‘only ‘define standards and frameworks. You ensure they are adopted, measurable and continuously improved. You will animate communities of practice, establish KPIs, monitor adoption, measure compliance, create feedback loops, identify improvement opportunities and report outcomes to technology leadership. Success is not achieved when standards are documen