Senior AI Solutions Consultant

About the Role

We are seeking a Senior AI Solutions Consultant to support the discovery, assessment, experimentation and adoption of Artificial Intelligence (AI) and Generative AI (GenAI) use cases across multiple business divisions.

This role is ideal for a techno-functional consultant who can operate at the intersection of business analysis, stakeholder engagement, AI solution design and rapid proof-of-concept (PoC) delivery. The successful candidate will work closely with business users, architects, engineers and technology partners to identify meaningful AI opportunities, translate business challenges into solution concepts and accelerate AI innovation initiatives.

The candidate should be comfortable navigating ambiguous problem spaces, facilitating stakeholder discussions and helping teams shape early-stage ideas into validated AI solutions.

Key Responsibilities

AI Use Case Discovery & Stakeholder Engagement

• Engage stakeholders across business, operational and corporate functions to understand challenges, process inefficiencies and opportunities for improvement.
• Facilitate workshops, interviews, design thinking sessions and discovery activities to identify AI and GenAI use cases.
• Analyse existing processes, systems, constraints and desired business outcomes.
• Assess and prioritise AI opportunities based on business value, feasibility, risks, data readiness and implementation complexity.
• Develop use case proposals, recommendations and presentation materials for management and project sponsors.

Requirements Analysis & Business Consulting

• Translate business and operational requirements into AI use cases, user journeys, process flows, user stories and functional specifications.
• Conduct current-state and future-state assessments to identify opportunities for AI-enabled automation, decision support, knowledge management and service improvements.
• Gather and document functional, non-functional, security, data and integration requirements for AI initiatives.
• Establish measurable success criteria for PoCs, including business, user adoption and technical outcomes.
• Act as a key liaison between business users, technical teams and governance stakeholders.

AI Solution Design & Prototyping

• Develop high-level AI solution designs, including solution approaches, target users, data requirements and integration considerations.
• Evaluate available technology options, including cloud platforms, enterprise technology stacks, open-source frameworks and custom-built solutions.
• Support rapid Proof-of-Concept (PoC) delivery through scope definition, prototype design, testing and validation activities.
• Collaborate with engineering teams to assess solution feasibility, scalability, security and operational readiness.
• Produce solution documentation, architecture views, PoC findings and implementation recommendations.

Requirements

Qualifications & Experience

• Bachelor's Degree in Computer Science, Information Systems, Data Science, Engineering, Artificial Intelligence or a related discipline.
• At least 5 years of experience in Business Analysis, Solution Consulting, Product Consulting, Solution Architecture, Digital Transformation or related technology roles.
• At least 3 years of hands-on experience in AI, Machine Learning (ML) or Generative AI (GenAI) initiatives, including use case discovery, experimentation, solution design, PoC development or implementation support.
• Proven ability to engage senior business stakeholders and technical teams, facilitate workshops and translate business requirements into practical solutions.
• Experience working in Agile or iterative delivery environments, including backlog refinement, user story development and stakeholder validation.
• Experience within healthcare, public sector, government agencies or regulated industries will be an advantage.

Technical Skills & Knowledge

• Experience working with cloud environments and enterprise technology platforms.
• Strong understanding of AI and GenAI technologies, including: Large Language Models (LLMs)Foundation ModelsRetrieval-Augmented Generation (RAG)AI Agents; Semantic Search; Document Intelligence; Natural Language Processing (NLP)Model Training and Deployment; Responsible AI practices
• Experience with cloud platforms such as AWS, Microsoft Azure, Google Cloud Platform (GCP) or equivalent.
• Understanding of cloud-native architecture, APIs, secure system integration, identity and access management, monitoring and DevSecOps practices.
• Familiarity with cybersecurity, privacy, governance and compliance considerations applicable to AI solution development within regulated environments.

Preferred Certifications

The following certifications will be advantageous:

• AWS Certified AI Practitioner
• AWS Certified Solutions Architect
• Microsoft Azure AI Engineer Associate
• Microsoft Azure Solutions Architect Expert
• Google Professional Machine Learning Engineer
• Scrum, SAFe, Design Thinking, Product Management or Business Analysis certifications