Technology Architect ( AI Platform)

Your purpose at Stanley/Stella

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

• .
• Your role and impact
• “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 documented. Success is achieved when they are adopted, measured, challenged and continuously improved across the organisation.

What Matters

• You ensure that data capabilities evolve in a way that supports AI adoption and agent-based architectures working closely with Data Lead.
• You have a strong appreciation for security, resilience and operational excellence.
• About you

You

• likely started
• your career as a software engineer,
• developer
• or technical lead bef
• ore evolv
• ing into architecture and technology leadership roles.
• You understand what it takes to build, integrate,
• deploy

and

• operate
• real-world systems because you have done it yourself.
• You combine hands-on technical credibility with the ability to step back, structure complex
• problems
• and design sustainable enterprise foundations.
• You are equally comfortable discussing APIs, integration patterns, cloud platforms, modern web technologies, front-end architectures, data architectures, AI
• frameworks
• and business priorities.
• You have enough software engineering experience
• to credibly
• challenge
• architecture decisions across front-end, back-end, integration,
• cloud
• and AI domains.
• Most importantly, you are pragmatic

• y
• ou
• distinguish sustainable enterprise capabilities from short-lived technology trends and make recommendations based on business value, scalability,
• maintainability
• and long-term impact rather than hype.

Potential

You will not be measured by the number of chatbots you build, but by your ability to establish the architecture, platforms, standards and operating models that allow Stanley/Stella to scale AI and modern engineering practices consistently across the enterprise.