AI Engineering Solutions Architect

• 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. 

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

• Demonstrated experience leading enterprise discovery or design workshops. 

• Certifications such as LUMA, IDEO, IBM Enterprise Design Thinking, Microsoft Catalyst, or equivalent structured problem solving frameworks. 

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

• Exposure to Prosci or similar change management methodologies. 

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

• Ability to steer conversations past feature requests into true needs and drivers. 

• Writes clear, enforceable scopes with realistic boundaries and measurable outcomes. 

• Comfortable whiteboarding and defending designs across Azure + Data + AI + Security + Power Platform. 

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

• Clear, concise, and credible with executive stakeholders. 
• 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. 

Cyclotron is an Equal Opportunity Employer. Cyclotron values diversity, equity and inclusion, and aims to practice DE&I in all that we do.