Trevor B.

For most of my career, I have been hired to solve problems that do not fit neatly inside one software platform, one department, or one job description. I am an Enterprise Solution Architect. I design both systems and processes. That means I work where business requirements, people, workflows, software, data, APIs, CRM, automation, AI, sales, marketing and operations intersect. Sometimes the problem is technical. Sometimes it is operational. Most of the time, it is both. My job is to understand how the business actually works, identify where friction, waste, risk or constraint exists, redesign the process where necessary, and determine what technology should support it. A CRM is not a solution. An API is not a solution. An AI model is not a solution. An automation is not a solution. And technology cannot fix a bad process. They are components. The real solution is the architecture: the processes, workflows, decisions, systems, data, integrations and people working together to produce the intended business result. Over the past decade, much of my work on Upwork has looked exactly like this even when the job title did not say “Solution Architect.” Clients have hired me for CRM, RevOps, marketing technology, HubSpot, Marketo, integrations, automation, process design, digital platforms and technical consulting. That work has included: • Migrating 200K+ contacts from Marketo to HubSpot with zero data loss • Reducing CAC by 40% through CRM-driven funnel optimization • Increasing MQL-to-SQL conversion by 35% through lead scoring and automation • Building autonomous buyer-intent systems • Designing AI-enabled operational workflows • Architecting software that replaces fragmented SaaS processes AI has now made me substantially more capable at the same work. Not because I suddenly became an “AI expert.” Because AI is an extraordinary force multiplier for an experienced architect. I can investigate unfamiliar systems faster, analyze business processes, interrogate documentation, map workflows, prototype integrations, write and review code, identify edge cases, generate documentation, test assumptions and move from an ambiguous business problem toward a working solution much faster than was previously practical. But the important decisions remain architectural. What process should exist? What should be eliminated? What should be standardized? What should be automated? What should remain human? What should be built? What should be bought? What should be integrated? Where should AI be used? Where should it not be used? I am most useful when the problem is still messy. You know something needs to change, but the answer is not simply “implement HubSpot,” “build an AI agent,” “connect these APIs,” or “hire a developer.” That is usually where I start.