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About the Role

Our client is embarking on a strategic AI transformation across its retail operations, supply chain, and corporate functions. The business requires an experienced AI Solution Architect to lead the design, governance, and enterprise-wide deployment of AI capabilities - ensuring that tools are adopted responsibly, costs are controlled, and measurable value is delivered at scale.

This is a senior, hands-on role that sits at the intersection of enterprise architecture, AI engineering, and organisational change. The successful candidate will be the primary authority on how AI is built, governed, and consumed across the ecosystem - from Tier 1 stores through to group-level corporate and supply chain functions.

Key Responsibilities

AI Strategy & Architecture

Design and own the enterprise AI reference architecture, aligning with technology strategy and long-term digital roadmap.Evaluate and recommend AI platforms, foundation models, and vendor tools - balancing capability, cost, data sovereignty, and vendor lock-in risk.Define patterns for model deployment including cloud, on-premise, and edge scenarios relevant to retail environments.Lead proof-of-concept and pilot engagements, translating business problems into viable AI solution designs.

Governance & Best Practice

Establish and enforce an AI governance framework covering model risk, data privacy, bias, auditability, and compliance (POPIA, relevant SA and international standards).Define the AI operating model: tooling standards, development workflows, model lifecycle management, and responsible use policies.Create and maintain AI policy documentation, architecture decision records, and solution design templates.Serve as the internal AI ethics and assurance checkpoint for new use cases before production deployment.

Cost & Usage Management

Implement FinOps practices for AI workloads - API usage tracking, model inference cost optimisation, and budget governance across teams.Define token/compute budgets per business unit and establish showback/chargeback mechanisms where applicable.Identify opportunities to reduce cost through model selection, prompt engineering, caching, and RAG architectures versus full fine-tuning.Provide regular reporting on AI spend, utilisation, and ROI to senior stakeholders.

Implementation & Enablement

Lead cross-functional delivery teams in building AI-powered solutions across retail operations, supply chain, HR, and customer experience.Collaborate with data engineering and platform teams to ensure clean, governed data pipelines that underpin AI initiatives.Define integration patterns for AI capabilities within existing enterprise systems (ERP, WMS, CRM, e-commerce platforms).Drive internal capability uplift - mentoring engineers, running enablement sessions, and building an internal AI community of practice.

Required Skills & Experience

Technical

Deep expertise in AI/ML solution design including LLMs, GenAI, classical ML, and computer vision use cases.Hands-on experience with major AI platforms and tooling (Azure OpenAI, Claude, CoPilot, Hugging Face, Langchain/LlamaIndex).Proficiency in Python and at least one cloud-native AI/ML stack (MLflow, SageMaker, Azure ML, Vertex AI Pipelines).Strong understanding of RAG architectures, vector databases (Pinecone, Weaviate, PGVector), embedding strategies, and agentic frameworks.Experience with enterprise integration patterns (APIs, event streaming, microservices) and deploying AI within complex system landscapes.Familiarity with AI observability, model monitoring, and MLOps tooling.

Architecture & Governance

Proven track record designing AI solutions at enterprise scale, with responsibility for architecture governance and standards.Experience implementing AI governance frameworks, responsible AI policies, and risk controls in regulated or high-compliance environments.Familiarity with South African regulatory context (POPIA) and international AI risk frameworks (EU AI Act, NIST AI RMF) is advantageous.

Domain & Sector

Retail, FMCG, or supply chain experience strongly preferred - familiarity with store operations, demand forecasting, and last-mile logistics is a significant advantage.Experience deploying AI in organisations with distributed, franchise, or wholesale operating models is a differentiator.

Soft Skills & Leadership

Ability to engage credibly with both technical teams and executive stakeholders - translating between business value and technical complexity.Strong communication skills - able to produce clear architecture documentation, business cases, and executive briefings.Comfortable operating in ambiguity and shaping the role alongside business leadership.Collaborative, pragmatic approach - focused on delivering working solutions, not just architecture artefacts.

Qualifications

Degree in Computer Science, Information Systems, Engineering, or related field (or equivalent demonstrated experience).Relevant certifications advantageous: AWS/Azure/GCP AI or Solutions Architect certification; TOGAF or equivalent enterprise architecture qualification.10+ years of experience in solution architecture or data/AI engineering, with at least 3 years focused on AI/ML implementation.

Ideal Candidate Profile

The ideal candidate has moved beyond being a practitioner and is now shaping AI strategy for large organisations. They understand what it means to govern AI at scale - not just build it. They are commercially aware, can hold a conversation about cost optimisation in the morning and model architecture in the afternoon, and are equally comfortable in a boardroom and a technical design session.

Prior consulting or advisory exposure is an asset given the breadth of this role. Experience in South African enterprise environments - especially those with franchise, wholesale, or distributed store networks - will significantly reduce the ramp-up period.

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