AI Solution Architect

About the role

IQbusiness is seeking a senior AI Solution Architect to lead the design and delivery of enterprise‑grade AI and Generative AI solutions across cloud platforms. The role blends solution architecture, AI engineering guidance and client‑facing consulting to translate complex business problems into scalable, production‑ready AI systems.

Key responsibilities

• Design end‑to‑end AI architectures covering data, application and integration layers, including Generative AI (LLMs, RAG, agents) and document intelligence.
• Lead client discovery workshops, define use‑case roadmaps and advise on build‑vs‑buy, risk and ROI considerations.
• Own architecture throughout the delivery lifecycle – from discovery and design to deployment, optimisation and governance.
• Architect solutions on at least one hyperscaler (Azure preferred) and define deployment patterns such as APIs, micro‑services and serverless functions.
• Design data foundations for AI, including pipelines, vector databases, embeddings and retrieval strategies.
• Support pre‑sales activities: solution design for proposals, effort estimation and client demos.
• Develop reference architectures, mentor engineers and contribute to internal AI capability building.

Required profile

• 7‑12+ years of technology, data or solution architecture experience, with 3‑5+ years in consulting or client‑facing roles.
• Proven track record leading AI or data engagements and managing multidisciplinary teams.
• Strong commercial acumen, ability to communicate with C‑suite and senior stakeholders.

Required skills

• Azure services: OpenAI, AI Foundry, AI Search, Document Intelligence, Synapse, Data Lake, App Services.
• AWS services: Bedrock, Lambda, S3.
• Google Cloud services: Vertex AI, Cloud Run.
• Design of distributed systems, micro‑services, API‑driven integrations and serverless architectures.
• Data engineering concepts: pipelines, lakehouse, vector databases, embeddings, retrieval‑augmented generation (RAG).
• Generative AI technologies: LLMs, prompt engineering, AI agents, evaluation guardrails.
• Security, governance and enterprise deployment models on cloud platforms.