AI Solution Architect

We are seeking an experienced AI Solution Architect to lead the design, architecture, and delivery of AI-powered solutions across client and internal projects. This role bridges business requirements, data science, software engineering, and cloud infrastructure to create scalable, secure, and production-ready AI systems., Solution Architecture & Design

• Lead discovery workshops and requirements gathering with stakeholders.
• Design end-to-end AI solution architectures for Generative AI, Machine Learning, and Intelligent Automation initiatives.
• Define system integration patterns across enterprise applications, APIs, databases, and cloud services.
• Create technical architecture diagrams, solution designs, and implementation roadmaps.
• Evaluate AI technologies, platforms, and frameworks to recommend best-fit solutions.

AI Strategy & Advisory

• Advise clients and internal stakeholders on AI adoption strategies and use cases.
• Conduct AI feasibility assessments, proof-of-concepts, and technology evaluations.
• Develop responsible AI frameworks covering bias evaluation, model explainability, data privacy, and regulatory compliance including the EU AI Act.
• Identify opportunities for process optimization through AI and automation.

Delivery Leadership

• Provide technical leadership throughout project lifecycles.
• Collaborate with AI/ML Engineers, Data Scientists, Software Engineers, and Product Teams.
• Review solution designs and ensure alignment with enterprise architecture standards.
• Support deployment planning, risk management, and solution scalability across full delivery lifecycle.

Stakeholder Management

• Present technical concepts to both technical and non-technical audiences.
• Engage with executive stakeholders to align AI initiatives with business objectives.
• Produce solution proposals, statements of work, and technical documentation., * Design and scale LLM-based applications, including multi-model routing, context management, and cost/latency optimisation. Prompt engineering strategies.
• Agentic AI systems.
• RAG design patterns, including chunking strategies, re-ranking, hybrid search, and evaluation
• Evaluation and monitoring frameworks covering hallucination detection, relevance scoring, and production drift monitoring.
• AI safety, governance, and compliance.

Human-Centred AI Design

• Trust architecture: design confidence scoring and uncertainty communication frameworks so users understand when AI is offering a recommendation versus a definitive answer; implement explainability mechanisms that build trust through transparency whilst maintaining appropriate scepticism about AI outputs.
• Human oversight: define clear automation boundaries distinguishing fully automated processes from human-in-the-loop workflows; mandate human review pathways for high-risk decisions in line with EU AI Act requirements.
• Feedback and control: design mechanisms enabling users to challenge, correct, or escalate AI-informed decisions.

The ideal candidate combines strong technical expertise with stakeholder management skills and can translate business challenges into practical AI solutions that deliver measurable value., Technical Skills

• Strong understanding of Machine Learning and Generative AI architectures.
• Experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
• Knowledge of AI orchestration frameworks such as:
• LangChain
• LlamaIndex
• Semantic Kernel
• CrewAI
• Cloud platform expertise in one or more of these areas:
• AWS
• Microsoft Azure
• Google Cloud Platform
• API design and microservices architecture.
• Data architecture and integration experience.
• Familiarity with knowledge graphs, vector databases and knowledge management systems., * 7+ years in software engineering, solution architecture, data engineering, or AI-related roles.
• 3+ years designing enterprise AI or ML solutions.
• Experience leading cross-functional teams and client engagements.