Microsoft AI Pre-sales Architect

• Shape solutions with clients. Lead discovery sessions and workshops, clarify the underlying client need and translate business ambitions into concrete AI use cases, solution directions and architecture principles.
• Design the initial architecture. Develop solution outlines, high-level designs and target architectures covering AI, agents, data, cloud, integration, security, governance and operational requirements.
• Make the solution deliverable. Translate architecture into scope, roles, phasing, effort, planning, cost assumptions, dependencies and technical risks. Test whether the commercial assumptions are realistic.
• Create compelling proposals. Work with bid managers, partners and account teams on RFPs, RFIs, tenders, proposals and presentations. Explain the solution clearly to both technical and non-technical stakeholders.
• Apply early quality controls. Support technical design and delivery reviews to validate feasibility, completeness, delivery approach, estimates, risks and architecture before a proposal is submitted.
• Challenge when necessary. Be prepared to say when a proposed scope, timeline, architecture or commercial assumption is not feasible, and offer a more realistic alternative.
• Maintain continuity after the win. Transfer architectural decisions, assumptions, dependencies and risks to the delivery architect and delivery lead, and remain involved during mobilisation and the initial implementation phase.
• Build reusable assets. Turn lessons from pursuits into reusable reference architectures, estimation approaches, templates, demonstrations and other assets that improve future sales and delivery.
• Collaborate with Microsoft. Connect client needs to relevant Microsoft platform capabilities and work with Microsoft teams on joint solutioning and a consistent end-to-end platform story.
   

You do not need hands-on expertise in every Microsoft product. We are looking for depth in a relevant part of the landscape, combined with enough breadth to make end-to-end architecture decisions and involve the right specialists. At architecture level, you should be comfortable with several of the following areas:

• Microsoft Foundry, Azure OpenAI, Copilot Studio and agentic AI patterns
• Microsoft 365 Copilot and AI-enabled workplace solutions
• Microsoft Fabric (including Fabric Apps and Agents in Fabric), data engineering, data products and enterprise intelligence
• Microsoft IQ: Fabric IQ, Foundry IQ and Work IQ
• RAG, enterprise knowledge architecture, model selection and AI evaluation
• Azure architecture, landing zones, databases and infrastructure modernisation
• Integration patterns, APIs, event-driven architectures and enterprise applications
• Power Platform
• Microsoft Agent365, Entra, Purview, Defender and security and governance by design
• Github & Github Copilot
• AI platform operations, monitoring, resilience and cost management
• Infrastructure as Code, CI/CD, containers and modern engineering practices
• Open models, open standards and integration with non-Microsoft platforms where required

Do you thrive on turning ambitious AI opportunities into winning solutions that balance innovation, commercial value, and delivery excellence? Can you translate complex client challenges into scalable Microsoft AI architectures, shaping proposals that are both compelling and realistically executable? Join KPMG as a Microsoft AI & Data Pre-Sales Architect and play a key role in helping clients unlock the full potential of AI through innovative, commercially sound, and deliverable solutions.