AI Engineering Presales Architect

Location: Remote (US) 
Department: Unified AI
Employment Type: Full-Time 
Rate: Base salary plus quarterly bonus

About the Role 

We’re looking for an AI Engineering Presales Architect who combines strong technical credibility with exceptional discovery, solution shaping, and executive communication skills. You will lead early-stage engagements, uncover true business drivers, and design responsible, scalable solutions across the Microsoft cloud ecosystem. 

If you thrive at the intersection of AI, cloud architecture, and consulting strategy—this is the role for you. 

Core Responsibilities 

• Lead 60–120 minute enterprise discovery sessions that surface true drivers, constraints, and decision dynamics. 

• Challenge client assumptions respectfully and reframe feature requests into business problems + measurable outcomes. 

• Architect credible solutions across Azure, Data, AI, Security, Integration, and Power Platform. 

• Produce high-quality SOWs, scopes, assumptions, dependencies, and change-control language. 

• Design phased delivery approaches that de-risk early (data readiness, feasibility, security constraints). 

• Communicate effectively with CFO/COO audiences (value, impact, risk) and CTO/CISO audiences (architecture, feasibility). 

• Shape engagements that balance margin, utilization, and delivery risk. 

• Partner with sales and delivery for clean handoffs and deal readiness. 

• Translate AI/Copilot/automation requests into clearly defined problems, measurable outcomes, and value hypotheses. 

• Support sales, delivery, and leadership through clean handoffs and deal orchestration. 

• Protect delivery teams by identifying risks, gaps, and misaligned client expectations early. 

Must-Have Core Skills 

• Deliverables Production: Produces high-quality SOWs, 1–2 page discovery summaries, phased delivery plans with gates, and DevOps-ready backlogs with estimates and assumptions 

• Enterprise Discovery Leadership: Ability to steer conversations past feature requests into true needs and drivers. 

• SOW + Scope Engineering: Writes clear, enforceable scopes with realistic boundaries and measurable outcomes. 

• Microsoft Architecture Breadth: Comfortable whiteboarding and defending designs across Azure + Data + AI + Security + Power Platform. 

• Consulting Economics: Understands margin, utilization, fixed-fee vs T&M, and risk structuring. 

• Executive Communication: Clear, concise, and credible with executive stakeholders. 

Technical Expertise (Microsoft Stack) 

• Azure data platforms: Fabric, Synapse, Data Lake, Data Factory. 

• Applied AI: Azure OpenAI (RAG, agents, summarization), Azure AI Search, evaluation strategies. 

• Integration patterns: APIM, Event Grid, Functions, Logic Apps, Container Apps. 

• Power Platform & Copilot Studio: when to use, when not to, and governance considerations. 

Preferred Background 

Candidates often come from Microsoft-focused consulting environments (e.g., Avanade, Slalom, EY, Deloitte, Accenture) with experience as: 

• Solution Architect 

• Engagement Lead 

• AI/Data/Cloud Architect 

• Pre-Sales Engineer or Advisory Consultant 

Qualifications  

• Experience: 8+ years in Microsoft cloud, data, or application architecture; 3–5 years in pre-sales, advisory, or solution architecture roles. 

• Discovery & Workshop Facilitation: Demonstrated experience leading enterprise discovery or design workshops. 

• Design Thinking (Preferred): Certifications such as LUMA, IDEO, IBM Enterprise Design Thinking, Microsoft Catalyst, or equivalent structured problemsolving frameworks. 

• Consulting Background: Prior experience at a Microsoft-focused consulting partner (e.g., Avanade, Slalom, Deloitte, EY, Accenture) strongly preferred. 

• Change & Adoption (Preferred): Exposure to Prosci or similar change management methodologies. 

Preferred Behavioral Traits 

• Intellectually honest; doesn’t bluff or oversell. 

• Direct but respectful—able to challenge clients constructively. 

• Structured operator: agendas, follow-ups, clarity, commitments. 

• Protects delivery teams through realistic scoping and expectations. 

• Builds lasting trust through clarity and value-first thinking.