Revenue Operations & GTM AI Architect · Vancouver, BC
Most enterprise AI dies in pilot. I architect the systems that do not: agent orchestration, evaluation and guardrails, integration and data architecture, containerized deployment. Then I stay embedded until the client team can run it without me.
~60%
reduction in manual lead qualification effort
120,000+
qualified leads generated for a fintech client
$5M
in HubSpot license and services revenue built
15+
years building revenue systems
For the past three years I have designed and deployed production AI inside live business operations. Agentic workflows that act on real records in real systems of record and keep running after handoff. That means the whole depth of the problem, not just the model: mapping the process, modelling the data underneath it, designing the orchestration and integration layer, defining evaluation criteria before launch, containerizing and deploying the services, and staying embedded until the client team can run it without me.
What I have learned is that AI projects almost never fail on model capability. They fail on the process nobody mapped, the data nobody cleaned, the failure mode nobody planned for, and the handoff nobody designed.
That is where my background is an advantage rather than a detour. I spent 15+ years building revenue engines across SaaS, fintech, and EdTech before I started automating them. So I scope against what a business can actually absorb, not against what a model can theoretically do.
I work embedded. Discovery, data readiness, architecture, build, integration testing, enablement, handoff. I would rather ship a working system and be measured on whether it holds up in month six than deliver a recommendation and leave.
Problem
Client revenue teams were spending hours a week manually qualifying and routing leads.
Built
Agentic workflows across HubSpot Breeze AI and self-hosted n8n covering scoring, enrichment, routing, and follow-up, with human review checkpoints, confidence thresholds, and escalation rules defined before launch.
Outcome
Roughly 60% reduction in manual lead qualification effort and faster MQL to SQL conversion.
Problem
A lending business needing qualified volume at a workable acquisition cost.
Built
An end-to-end organic search and conversion system, as external consultant alongside their Head of Marketing.
Outcome
20M+ organic visits and 120,000+ qualified leads, converting at 10% into 12,000+ funded credits.
Problem
Mid-market companies buying CRM software and failing to operationalize it.
Built
An implementation practice covering CRM architecture, migration, onboarding, automation design, and ongoing optimization.
Outcome
Over $5M in HubSpot license revenue and $10M in related services.
Multi-step workflows across HubSpot Breeze AI and self-hosted n8n. Tool and API calls, conditional routing, state handling between steps, human-in-the-loop checkpoints, retry logic, escalation paths.
Acceptance criteria, edge-case test sets, and confidence thresholds defined before launch, with output review instrumented so failures surface as measurable regressions rather than client complaints.
REST and webhook integrations, event-driven triggers, MCP connectors, data sync and enrichment, and idempotent write patterns that protect the integrity of the system of record.
Object relationships, custom properties, lifecycle stages, and attribution logic modelled so automated decisions run on clean, structured context.
Self-hosted workloads in Podman containers, front-end and serverless services on Vercel, version-controlled configuration, environment separation, documented rollback paths.
Embedded through discovery, data readiness assessment, architecture, build, integration testing, enablement, and handoff.
I also architected and shipped Toko, a children's financial literacy application, from problem validation through data model, build oversight, and production deployment.
Six operating companies under DGY Group, covering revenue operations, AI development, media, and product.
Designing and deploying production agentic systems inside live client operations, from data readiness through handoff.
Setting technical direction and delivery standards across the six operating companies.
Built the revenue operations and HubSpot solutions practice serving clients across North America and Latin America.
Led international market entry for a K-12 EdTech platform across four regions.
Built the sales and marketing function and the channel programme for an education software suite.
Taught postgraduate diplomas in strategic digital marketing and inbound.
Contact
Open to AI solutions architect, applied AI, and forward deployed roles. Based in Vancouver, open to remote and hybrid, and available to travel for client engagements.
r@robayala.com
LinkedIn