AI Enablement Designer

We are hiring for AI Enablement Designer at Knutsford, UK – 3 days per week Onsite Role Overview • We are looking for an AI Enablement Designer with strong experience in systems integration to help design, shape, and enable AI powered capabilities across our organisation. This role sits at the intersection of solution design, AI adoption, and integration engineering — ensuring AI tools, platforms, and workflows seamlessly connect into existing systems and deliver real business value. • You will work with product teams, engineers, architects, data specialists, and business stakeholders to design AI enabled solutions, integration patterns, and adoption pathways that are secure, scalable, and aligned to enterprise strategy. Key Responsibilities AI Solution & Enablement Design • Design AI enabled workflows, features, and capabilities that integrate into existing technology estates and business processes. • Translate business needs into clear AI solution concepts, including user journeys, functional designs, and technical enablement requirements. • Define the architecture and integration patterns required for AI services (e.g., LLMs, copilots, automation tools) to work effectively within enterprise systems. Systems Integration (SI) Enablement • Work closely with engineering and integration teams to define how AI components interface with APIs, data pipelines, applications, and cloud platforms. • Develop integration design artefacts, including interface specifications, mapping documents, and workflow diagrams. • Ensure AI services are integrated using secure, resilient, and scalable patterns aligned to enterprise standards. • Support teams implementing these integrations by providing clear design guidance and technical oversight. Governance, Risk & Assurance • Ensure AI enablement designs meet security, data privacy, compliance, and responsible AI requirements. • Support risk assessments, responsible AI reviews, and mitigation planning. • Contribute to design governance forums and ensure alignment with enterprise architecture and AI strategy. Collaboration & Stakeholder Engagement • Partner with product owners, architects, engineering teams, and business SMEs to co create AI solutions. • Facilitate workshops to define use cases, capture requirements, and map integration needs. • Communicate AI concepts and design decisions clearly to both technical and non-technical stakeholders. Documentation & Standards • Produce high quality design documentation, including solution designs, integration specs, process flows, and user enablement guides. • Help develop reusable AI and SI design patterns, standards, and best practices. • Maintain accurate documentation throughout delivery and support continuous improvement. Skills & Experience Essential • Experience designing or supporting AI enabled solutions, such as LLM integrations, copilots, automation tools, or intelligent workflows. • Strong understanding of system integration concepts: APIs, event driven design, data ingestion, microservices, and cloud integration. • Ability to translate business needs into clear design artefacts and logical technical requirements. • Understanding of enterprise data flows, data models, and how AI applications consume and produce data. • Experience working with cloud platforms (Azure, AWS, or GCP) and their AI and integration services. • Strong analytical, conceptual, and problem solving skills with the ability to simplify complex systems. Preferred • Familiarity with AI governance, responsible AI frameworks, and data privacy considerations. • Experience in environments with large and complex legacy systems that require thoughtful integration approaches. • Exposure to MLOps, prompt engineering, vector databases, or modern AI tooling. • Understanding of enterprise architecture frameworks and design governance. • Certifications in AI, cloud architecture, or integration technologies. Personal Attributes • Clear communicator who can explain technical concepts at the right level for each audience. • Collaborative and comfortable working across multidisciplinary teams. • Curious, adaptable, and motivated to keep up with rapidly evolving AI technologies. • Detail oriented but pragmatic, with the ability to design solutions that are feasible and value driven. • Proactive in identifying risks, challenges, and opportunities for improvement.