AI Solutions Architect (Fraud and Cyber focus)

Join us as an AI Solutions Architect

As the Solution Architecture Leader, you will lead the design and delivery of Fraud and Cyber AI systems.

Working within the AI Hub Architecture team, this role partners closely with stakeholders and subject matter experts to shape technology.

Your key responsibilities will include

• Providing solution design services in support of prioritised AI use cases, from early engagement through to delivery assurance.
• Designing high-quality solutions that are innovative, scalable, stable and resilient, conforming to architectural principles, security policies, and regulatory requirements.
• Ensuring solutions meet non-functional requirements including performance, availability, disaster recovery, and observability.
• Contributing to the ownership and evolution of governance, assurance frameworks, standards, and policies with a focus on improving design quality and consistency.
• Defining high-level transition plans to address gaps between current and future state, aligned to IT budgeting and planning processes.
• Leading analysis of the current technology environment.
• Overseeing and supporting the research, evaluation, and selection of new software technologies, platforms, and architecture standards.
• Embedding Responsible AI, security, privacy and regulatory requirements into architecture (controls, model risk, auditability, human-in-the-loop), working with Risk, Security and Compliance.

What you will bring to the role

• Experience of design and implementation of Cloud-based applications and services.
• Experience of creating application migration strategies, enabling transition away from legacy technologies.
• Experience of creating and selling a business case for technology investment.
• Track record of architecting modern platforms using APIs, EAI, ETL and web services.
• Experience in solution or enterprise architecture, including designing and delivering production AI, machine learning or large-scale distributed systems.
• Hands-on expertise with Large Language Models, retrieval-augmented generation, agentic and orchestration frameworks, and vector databases.
• A strong command of at least one major cloud platform (Amazon Web Services, Microsoft Azure) and of software engineering best practice, APIs, security, and MLOps or LLMOps.
• Working knowledge of AI governance, security, privacy and Responsible AI practices such as fairness, transparency and accountability.

Next steps

Computershare are dedicated to providing you with the opportunity to succeed on your own merits, starting from the application process.

Our goal is to create an environment where everyone feels valued, to remove barriers and obstacles and ensure equal opportunities for all.