AI Solution Architect

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Job Description

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.

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

Key Responsibilities

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.

Qualifications

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.

Generative AI Experience

• 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.

Professional Experience

• 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.