Sparkd - AI for Business Growth

• Design and document end-to-end cloud architectures on Azure for financial services clients, taking ownership of service selection, cost optimisation, and compliance considerations. • Act as the primary technical point of contact with client engineering and infrastructure teams, leading architecture discussions and translating business requirements into concrete technical plans. • Work alongside ML engineers and backend developers to ensure that AI workloads, data pipelines, and APIs are deployed on infrastructure that meets enterprise and regulatory requirements. • Contribute to technical proposals and scoping documents for new client engagements, providing credible architectural estimates and risk assessments. • Identify and resolve infrastructure risks across active projects, particularly where data governance, latency, or compliance constraints are involved.