Role Overview Lead technical presales from discovery through solution design, demonstration and delivery handover. Azure expertise is mandatory. You will capture requirements independently of any vendor and map them to suitable cloud, data and AI technologies, including alternative platforms and open-source frameworks. This is a hands-on architect role. You will work closely with the BDM, founder and delivery specialists, build focused proofs of concept and make recommendations that are technically credible and achievable. KEY RESPONSIBILITIESDiscover the requirement Lead business and technical workshops. Document workflows, users, outcomes, data sources, integrations and non-functional requirements, including scale, latency, availability, security, residency and operating constraints. Design independently Create a vendor-neutral logical architecture, then map requirements to platform services and AI frameworks. Present alternatives with traceable decisions, dependencies and trade-offs. Demonstrate capability Build and present focused prototypes using approved data. Define success measures, test limitations and separate demonstration evidence from production readiness. Scope the engagement Produce solution proposals, RFP responses, architecture diagrams, effort estimates and statements of work. Agree assumptions, exclusions and acceptance criteria with delivery leads before making commitments. Work through partners Support SI and MSP discussions, technical objections and customer presentations. Respect agreed account boundaries and coordinate specialist input throughout the opportunity. REQUIRED EXPERIENCETypically 8 or more years in software, data or AI engineering, including at least 3 years in architecture or technical leadership with customer-facing responsibilities. Equivalent evidence of capability will be considered. Applications and integration: Design and deliver Azure applications using appropriate combinations of App Service, Functions, Container Apps, API Management, messaging, Azure SQL and Storage. Assess modernisation choices and justify when AKS is appropriate. Data architecture: Strong SQL and data modelling skills. Assess data quality and readiness, ingestion, ETL/ELT, batch and streaming needs, warehouses or lakehouses, semantic layers, lineage, access controls and retention. Relevant platforms include Microsoft Fabric, Databricks and Snoflake. Software engineering: Proficiency in Python and at least one application stack such as . NET/C#, Java or Type Script. Build APIs and integrations, work with relational and vector stores, use containers and infrastructure as code, and review automated tests. A record of delivering enterprise applications and practical AI solutions beyond a demonstration. Able to explain personal contributions, architecture choices, production issues and lessons learned. Experience translating ambiguous business needs into requirements, architectures and achievable delivery scopes. Strong written proposals and clear presentations to business and technical audiences. Ability to coordinate distributed delivery teams and validate estimates with specialists. Understand application support, release management, service transition and ongoing AI quality monitoring. A degree in computer science, engineering or a related discipline, or equivalent practical experience. Professional English communication is essential.