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
  • 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

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