AI Solution Architect

Our Client:

Our client is a global fintech leader building an inclusive and innovative payment ecosystem that connects digital wallets, acquirers, merchants, local and global payment systems, and emerging industry players. With significant scale, cross-border reach, and a product portfolio at the forefront of digital commerce, the organization is shaping how consumers and businesses pay across markets.

My client is looking for a seasoned AI Solution Architect to work directly with enterprise customers to identify AI opportunities, design scalable solutions, and lead technical delivery from initial discovery through production deployment and customer adoption.

This role combines solution architecture, AI engineering knowledge, technical consulting, and customer engagement. You will collaborate closely with enterprise clients, sales, product, and engineering teams to translate business challenges into practical AI solutions that deliver measurable business value.

Key Responsibilities:

1. Enterprise Customer Discovery and Consulting

• Lead customer discovery workshops to understand business objectives, operational challenges, technical requirements, and data readiness.

• Identify opportunities where AI can improve business processes, operational efficiency, and customer experience.

• Translate business requirements into technical solution concepts and implementation roadmaps.

• Engage with senior executives, business stakeholders, and technical teams to align expectations and solution objectives.

2. AI Solution Architecture and Design

• Design end-to-end AI solutions covering models, data pipelines, enterprise integrations, security, scalability, and infrastructure costs.

• Develop architectures incorporating LLMs, RAG, prompt engineering, model evaluation, and AI agent frameworks.

• Assess technical feasibility, data requirements, system dependencies, and potential implementation risks.

• Ensure solutions meet enterprise requirements for reliability, security, performance, and scalability.

3. Technical Pre-Sales and Solution Consulting

• Support the sales team throughout technical discovery and pre-sales engagements.

• Deliver technical presentations, product demonstrations, and solution proposals to enterprise customers.

• Prepare technical responses for Requests for Information (RFIs) and Requests for Proposals (RFPs).

• Develop solution architecture documentation, technical specifications, implementation plans, and cost estimates.

• Communicate complex AI concepts and technical capabilities in a clear and commercially relevant manner.

4. Proof of Concept and Solution Validation

• Lead Proof of Concept (POC) initiatives to validate proposed AI solutions.

• Define POC scope, implementation timelines, success criteria, and measurable business outcomes.

• Coordinate technical resources and customer stakeholders throughout the POC lifecycle.

• Evaluate solution performance, identify gaps, and recommend improvements before production implementation.

5. Technical Delivery and Implementation

• Own technical delivery from implementation planning through integration, testing, production deployment, and customer acceptance.

• Work closely with engineering and product teams to ensure solutions are implemented according to agreed technical specifications.

• Manage technical risks, dependencies, project timelines, and delivery milestones.

• Coordinate customer and internal teams to resolve technical challenges and maintain delivery progress.

• Oversee technical documentation, knowledge transfer, and operational handover to ensure successful customer adoption.

6. Cross-Functional Collaboration

• Partner with sales, product, and engineering teams to align customer requirements with product capabilities.

• Provide technical insights and customer feedback to influence product development and solution enhancements.

• Support enterprise customers throughout implementation and adoption.

• Establish strong working relationships with customer executives, IT teams, data teams, and other technical stakeholders.

Requirements:

• At least 6-15 years of relevant technical experience in solution architecture, AI engineering, technical consulting, enterprise technology, or related fields.

• Demonstrated experience designing and delivering AI solutions, including taking enterprise customer solutions into production.

• Proven experience engaging external enterprise customers in solution architecture, technical consulting, or technical pre-sales capacities.

• Practical knowledge and hands-on exposure to:

  • Large Language Models (LLMs)

  • Retrieval-Augmented Generation (RAG)

  • Prompt engineering and prompt design

  • Model evaluation and performance optimisation

  • AI agent architectures and orchestration

  • AI security and enterprise deployment considerations

• Strong understanding of API integration and enterprise system connectivity.

• Experience working with at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud Platform.

• Ability to translate business requirements into scalable technical architectures and implementation plans.

• Strong presentation, stakeholder management, and technical delivery coordination skills.

• Comfortable communicating with senior executives, business stakeholders, and technical engineering teams.

• Relevant university degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience.

EA Licence No: 23S1615