Microsoft AI Pre-sales Architect

Microsoft AI Pre-sales Architect

Location: Amstelveen, NH, nl

Our team helps clients use modern Microsoft platforms, trusted data and AI  work across the Microsoft ecosystem, from Azure and Fabric to Copilot, Copilot Studio and Microsoft Foundry, with security and governance embedded throughout.

As a Microsoft AI Pre-Sales Architect, you'll help organisations transform bold AI ambitions into achievable business outcomes. Combining deep Microsoft technology expertise with strong commercial insight, you'll design solutions that not only stand out during the sales process but also create long-term value for clients.

Rather than simply responding to client requirements, you'll help shape them. Discovery workshops, solution design, architecture definition, effort estimation, and commercial validation are all part of the role. By bringing together technical expertise, strategic thinking, and a strong understanding of delivery realities, you'll ensure every proposed solution is both differentiated and achievable.

• Lead with AI while keeping the full Microsoft platform in view.
• Connect Azure, data, AI, security, business applications and the digital workplace into one credible solution story.
• Start with industry and client outcomes rather than with technology alone.
• Use reusable architectures, accelerators and assets to improve speed, consistency and quality.
• Embed security, governance and trust into the solution from the start.
• Protect delivery quality through early qualification, technical validation and realistic delivery planning.
• Help clients move from pilots and isolated use cases towards scalable platform transformation.

• 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 Agent
  365, Entra, Purview, Defender and security and governance by design
• Github & Github Copilot
• AI platform operations, monitoring, resilience and cost…