AI Solution Architect

We are recruiting an AI Solutions Architect to lead the design and delivery of enterprise-grade AI and Generative AI solutions across cloud platforms, with a strong emphasis on production deployment, business value and consulting-led delivery.

This role sits at the intersection of

• Solution architecture (end-to-end systems design)
• AI engineering (capability awareness, not hands-on build ownership)
• Consulting (client engagement, commercial alignment, pre-sales)

The successful candidate will translate complex business problems into scalable AI architectures, lead multidisciplinary teams, and ensure AI solutions are aligned to enterprise systems, governance, and measurable outcomes.

Role Context & Positioning

• Senior member of the AI & Data capability working across multiple client engagements
• Acts as the bridge between AI engineering, architecture, and business stakeholders
• Owns solution design, architecture governance and delivery oversight
• Plays a key role in pre-sales, client shaping, and capability development

Responsibilities

AI Solution Architecture & Design

• Lead the design of end-to-end AI architectures across data, application and integration layers
• Design solutions spanning:
• Generative AI (LLMs, RAG, agents)
• Document intelligence and automation
• Enterprise AI platforms and APIs
• Define:
• Data flow, integration patterns, and system architecture
• Retrieval, orchestration and agent interaction patterns
• Security, governance and deployment architectures

Client Advisory & Solution Shaping

• Lead discovery workshops and use case definition sessions
• Translate business problems into AI-enabled solutions and architecture blueprints
• Advise clients on:
• AI adoption roadmaps
• Architecture approaches (build vs buy vs hybrid)
• Trade-offs, risks, and ROI

Delivery Leadership

Own architecture across delivery lifecycle: Discovery design build oversight deployment

• • optimisation
• Guide engineering teams on:
• Architecture decisions
• Design patterns and best practice
• Ensure:
• Production-grade delivery
• Alignment to enterprise systems and constraints

Cloud AI Architecture

• Architect solutions across at least one hyperscaler (Azure preferred), including:
• Azure OpenAI, AI Foundry, AI Search, Document Intelligence
• Equivalent AWS (Bedrock) or GCP (Vertex AI) services
• Define:
• Deployment patterns (APIs, microservices, serverless)
• Integration into enterprise ecosystems
• Security, networking and governance models

Data & AI Platform Design

• Design data foundations required for AI:
• Data pipelines, ingestion patterns, storage and modelling
• Vector databases, embeddings and retrieval strategies
• Ensure:
• Data quality, lineage, and governance alignment
• AI-readiness of enterprise data platforms

Pre-Sales & Commercial Contribution

• Support and lead:
• Solution design for proposals and RFPs
• Estimation, costing and effort modelling
• Contribute to:
• Client pitches and demos
• Opportunity shaping and deal conversion

Capability Building & Thought Leadership

• Develop:
• Reference architectures and reusable solution patterns
• Mentor:
• Engineers and consultants
• Contribute to:
• Internal capability development and AI maturity

Requirements

Consulting & Leadership

• 7–12+ years in technology, data or solution architecture
• 3–5+ years in consulting / client-facing architecture roles
• Proven experience:
• Leading AI or data engagements
• Managing multidisciplinary teams
• Engaging senior stakeholders and executives

AI & Generative AI

• Practical experience designing solutions involving:
• LLMs and Generative AI applications
• RAG architectures and retrieval systems
• AI agents / orchestration patterns
• Strong understanding of:
• Prompting, evaluation and guardrails
• Enterprise AI use cases and limitations

Solution Architecture

• Strong experience designing:
• Distributed systems and microservice architectures
• API-driven integrations
• Enterprise-scale cloud solutions
• Ability to clearly articulate architecture decisions and trade-offs

Cloud (At least one CSP, Azure preferred)

• Azure (preferred): OpenAI, AI Foundry, Synapse, Data Lake, App Services
• AWS: Bedrock, Lambda, S3
• GCP: Vertex AI, Cloud Run

Data & AI Platform Understanding

• Strong grounding in:
• Data engineering concepts (pipelines, modelling, lakehouse)
• AI system data flows (embeddings, chunking, indexing)
• Experience designing AI-ready data ecosystems

Business & Communication

• Ability to:
• Translate technical designs into business outcomes
• Communicate with C-suite and architecture boards
• Strong commercial acumen and delivery mindset

Please Note

As all iqbusiness roles require honesty in the handling of or access to cash, finances, financial systems, or confidential information; our recruitment process requires that the following background checks be completed: credit, criminal, ID, and qualification verification

iqbusiness is committed to sustainable growth and transformation, we embrace diversity and employ previously disadvantaged individuals