Presales Solutions Architect

Centrilogic

. Design cloud, AI and data architectures using the Microsoft stack from Azure infrastructure and networking through analytics and AI .

Posted 9/17/2026full-timeToronto • CanadaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing cloud, AI, and data architectures using the Microsoft stack, with a strong focus on Azure infrastructure, networking, and AI solutions. Proven ability to lead presales engagements, develop proposals, and advise clients on technical solutions and governance practices.

Highest-signal resume keywords

Azure Infrastructure ExperienceEnterprise AI Delivery ExperienceMicrosoft Certified: Azure Solutions Architect ExpertProposal Writing and SOW DevelopmentDiscovery Workshop Facilitation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud ArchitectureAzure NetworkingAI Solutions DesignData ModernizationAzure Migrate AssessmentsPower BIAzure SQLREST APIsAzure DevOpsTerraform

Soft Skills

Strong CommunicationClient AdvisoryCollaborative Problem Solving

Tools & Technologies

Microsoft 365 CopilotAzure AI FoundryMicrosoft FabricPower PlatformAzure OpenAI Service

Certifications & Qualifications

Microsoft Certified: Azure Solutions Architect Expert (AZ-305)Microsoft Certified: Azure AI Engineer Associate (AI-102)AZ-700DP-600

Industry Keywords

Cloud Solutions EngineeringTechnical ConsultingManaged ServicesData GovernanceResponsible AI

Tech Stack

Tools & technologies

AzureCloudDNSERPFirewallsPythonSQLTerraformVMware.NET

About the role

Key responsibilities & impact

Design cloud, AI and data architectures using the Microsoft stack from Azure infrastructure and networking through analytics and AI
Architect Azure landing zones, subscription and identity designs, IaaS and PaaS migration patterns, resiliency, disaster recovery and cost control
Design Azure networking topologies, connectivity, firewalls, segmentation, private endpoints and Private DNS
Design AI solutions using Azure AI Foundry, Azure OpenAI, Microsoft 365 Copilot and Copilot Studio, including agentic, RAG and multi-model patterns
Show clients how Microsoft Fabric and the wider Azure data estate support AI readiness through lakehouse, warehouse, Power BI and governance patterns
Incorporate Power Platform for workflow automation and reporting
Apply responsible AI practices covering content safety, data governance, model transparency and compliance
Size and scope engagements using ROM estimates and structured discovery
Advise clients on project delivery versus ongoing managed services across infrastructure, security and AI operations
Act as senior technical advisor to sales leadership, account teams and client stakeholders throughout the sales cycle
Hold discovery workshops and current-state assessments
Translate solutions into business terms, value narratives, ROI models and executive presentations
Advise clients on AI governance and productionizing AI workloads
Work with Account Executives to build and advance opportunities
Own technical responses for RFPs, competitive deals and executive briefings
Write proposals, effort estimates, pricing models and SOWs through review
Build proofs of concept and demos for client use cases
Develop business cases for cloud, AI, data and managed services
Use network and industry profile to open doors and generate pipeline
Collaborate with SMEs across cloud, data, security, ERP and managed services
Validate designs with delivery and implementation teams before proposals and remain involved at kickoff
Peer review proposals for accuracy, scope integrity and delivery fit
Improve the practice through reusable assets, internal enablement and reusable intellectual property
Lead qualified-opportunity discovery within the first 90 days
Own the technical narrative on pursuits by six months, contributing to win rate and deal progression
Produce executable proposals and SOWs and scalable reusable assets on an ongoing basis

Requirements

What you’ll need

University degree in computer science, engineering, information technology or an equivalent technical discipline
7+ years in cloud architecture, infrastructure engineering, cloud solutions engineering or technical consulting on the Microsoft stack
3+ years in presales, solution architecture or another customer-facing advisory role
Hands-on Azure infrastructure experience, including landing zones, server and workload migrations, hybrid connectivity and core Azure networking
Enterprise AI delivery experience, including Microsoft 365 Copilot rollouts, agents built in Copilot Studio or Azure AI Foundry, and RAG patterns
Microsoft Fabric or Azure data platform exposure sufficient to qualify data modernization or AI-readiness opportunities and scope discovery with a data specialist
Experience running discovery workshops, writing proposals, sizing engagements and presenting to executives
Record of deals won and advanced in a consultative technical presales role
Microsoft Certified: Azure Solutions Architect Expert (AZ-305), required or achieved within six months of hire
Microsoft Certified: Azure AI Engineer Associate (AI-102), required or achieved within six months of hire
Azure infrastructure and networking knowledge
Azure landing zones, management groups, subscription design, Azure Policy, RBAC and governance at scale
Compute, storage and platform services, including virtual machines, Azure VMware Solution, App Services, Container Apps, AKS, backup and disaster recovery
Core networking, including hub-and-spoke, Virtual WAN, ExpressRoute, VPN, Azure Firewall, NSGs, UDRs, private endpoints, Private DNS, Application Gateway and Front Door
Azure Migrate assessments, migration wave planning and Azure Arc
Entra ID, Conditional Access, Zero Trust and Defender for Cloud
Azure pricing and sizing, reservations, savings plans, CSP, EA and FinOps basics
Azure OpenAI Service, Azure AI Foundry, Microsoft 365 Copilot, Copilot Studio, Microsoft Agent Framework, Semantic Kernel and RAG architectures
Vector stores, embeddings and chunking strategies
Model Context Protocol and agent-to-agent interoperability
Responsible AI, content safety, data governance, fairness, model transparency and regulatory compliance
Microsoft Fabric, OneLake, lakehouse and warehouse patterns, Data Factory pipelines and Power BI semantic models
Azure SQL, Cosmos DB, Azure AI Search and Synapse-to-Fabric migration paths
Microsoft Purview, lineage, classification and sensitivity labelling
REST APIs, Azure Service Bus, Event Grid, Logic Apps and hybrid connectivity
Power Apps, Power Automate and Power BI
Solution selling, proposal writing, SOW development, effort estimation and pricing models
POC and demo design, including building or scripting one
Strong written and spoken communication with executives and architects
Willingness to travel within the Greater Toronto Area, elsewhere in Canada, and to the United States as needed
Preferred certifications: AZ-700, DP-600 and Microsoft Certified: Agentic AI Business Solutions Architect
Nice-to-have experience with Fabric or Synapse implementation, Sentinel, Defender for Cloud, Microsoft industry clouds, Anthropic Claude, C#/.NET, Python, Azure DevOps, GitHub Actions, Bicep, Terraform, LLMOps, MLOps, FinOps for AI, managed services design, Dynamics 365, Salesforce, JDE and NetSuite

Benefits

Comp & perks

Full-time employment
Opportunity to work with Azure, Microsoft 365, Copilot, Microsoft Fabric, AI and managed services
Opportunity to work with global clients and teams
Professional enablement through reusable assets, internal enablement and intellectual property development
Exposure to executive-level client engagements and enterprise consulting
Travel opportunities within the Greater Toronto Area, elsewhere in Canada, and to the United States as needed