Forward-Deployed AI Solutions Engineer
Not demos. Not proofs of concept. Production systems shipped inside $250M ARR organizations.
10+ years bridging customer context → technical architecture → measurable outcomes.
$250M
ARR org scope
13+
AI agents shipped to production
1,200+
Accounts scored & prioritized
15
Person team led & developed
Proof in Motion
Each run shows scope, orchestration, execution, and quality gate evidence in a dedicated modal workspace.
Simulation Workspace
You’ll see orchestration decisions, parallel work, and quality checks before final output.
Discovery
Ambiguous requirements → scoped execution plan.
Architecture
Multi-agent design with built-in guardrails.
Delivery
Production outputs, not prototype artifacts.
Selected Work
Each project is framed by business problem, implementation detail, and operational result.
What I built: Designed a state-managed RAG workflow synthesizing Salesforce, Gong, Zendesk, and Totango signals.
Result: Created earlier intervention windows and cleaner transitions for renewal-risk accounts.
Phase
Discovery → Delivery
Scale
1,200+ accounts org-wide
Result
Earlier risk intervention
What I built: Built a repeatable scoring model with CRM-ready outputs for engagement, risk, and expansion readiness.
Result: Improved focus for CSM execution across a $250M ARR organization.
Phase
Architecture
Scale
$250M ARR org-wide
Result
Execution focus lift
What I built: Shipped an internal planning app for ARR redistribution scenarios and handoff planning.
Result: Removed multi-day manual workflows and improved coverage planning quality.
Phase
Implementation
Scale
Territory planning
Result
Days → minutes
How I Work
Every engagement follows the same four-phase pattern — from ambiguous problem to production delivery.
Start with the customer's reality, not the technology. Map constraints, success criteria, and stakeholder context before writing a single line of code.
Signal
Requirements → clarity
Architecture that serves the experience, not the other way around. Multi-agent workflows with quality gates, human-in-the-loop checkpoints, and rollback paths.
Signal
Blueprint → guardrails
Ship production systems, not prototypes. Measurable outputs, documented runbooks, and stakeholder-ready reporting from day one.
Signal
Build → operational
Close the loop with quality monitoring, prioritization models, and continuous improvement. Systems that get better over time.
Signal
Measure → improve
Start with the customer's reality, not the technology. Map constraints, success criteria, and stakeholder context before writing a single line of code.
Signal
Requirements → clarity
Architecture that serves the experience, not the other way around. Multi-agent workflows with quality gates, human-in-the-loop checkpoints, and rollback paths.
Signal
Blueprint → guardrails
Ship production systems, not prototypes. Measurable outputs, documented runbooks, and stakeholder-ready reporting from day one.
Signal
Build → operational
Close the loop with quality monitoring, prioritization models, and continuous improvement. Systems that get better over time.
Signal
Measure → improve