Staff-level support systems for high-growth SaaS
Support breaking at scale?
I design the systems that fix it.
I design escalation governance, CRM architecture, routing logic, and support analytics that reduce unnecessary escalations, improve decision quality, and protect engineering time.
Senior individual contributor operating at the intersection of Support, Product, and Engineering.
Where I Add Leverage
Best suited for teams whose support complexity is outgrowing current systems.
- Engineering is pulled into avoidable escalations
- Severity definitions vary by team or manager
- Zendesk or Salesforce exists but is not fully trusted
- Dashboards exist but are not driving decisions
- Support is blamed for product gaps without shared frameworks
10+ Years
Support Operations experience across enterprise and high-growth SaaS environments.
Zendesk Certified
Deep hands-on experience in administration, workflow design, analytics, and self-service systems.
Systems + Execution
Comfortable moving from operating models and architecture to implementation details and reporting.
Cross-Functional
Designed frameworks that align Support, Product, Engineering, and Operations.
When Teams Bring Me In
I add the most leverage when support is growing faster than the systems behind it.
I work best in environments with real customer complexity, rising operational pressure, and a need for stronger support infrastructure without unnecessary bureaucracy.
Escalation chaos
Engineering is getting pulled into issues too early, too often, or without shared severity criteria.
Tooling without trust
Zendesk or Salesforce is live, but workflows do not reflect reality and confidence in the system is low.
Reporting without decisions
Leaders have dashboards, but not the visibility needed to manage backlog risk, escalation patterns, or accountability.
Support blamed for product gaps
There is no shared framework for translating customer pain into prioritization, routing, and feedback loops.
What I Build
I do not just improve workflows. I design the operating systems behind scalable support.
My strongest work lives where Support, Product, Engineering, and Operations need clearer structure, stronger governance, and systems that can be trusted as the company grows.
Escalation Governance
Build clear severity models, escalation criteria, and RCA frameworks that reduce ambiguity and protect engineering bandwidth.
- Severity design and standardization
- Objective escalation thresholds
- SLA and customer impact alignment
- RCA workflows and recurrence tracking
- Policy-to-workflow implementation
CRM and Workflow Architecture
Design Zendesk and Salesforce systems that reflect how teams actually work, not just how the tool ships.
- Routing logic and automation strategy
- Form and field architecture
- Queue and escalation design
- Cross-functional workflow integration
- Documentation and release governance
Support Analytics and Observability
Turn support data into decision-making infrastructure leaders can use to prioritize action and measure operational health.
- Executive dashboards
- KPI alignment across teams
- Escalation trend visibility
- Backlog and capacity reporting
- Product and Engineering feedback loops
AI-Ready Support Foundations
Prepare support organizations for AI-first operations with better knowledge architecture, safe handoffs, and stronger governance.
- Knowledge architecture for containment
- Automation readiness
- AI-to-human escalation logic
- Governance and quality guardrails
- Deflection and containment measurement
I focus on systems that improve decision quality, reduce avoidable escalations, and make support organizations more scalable.
What Happens When You Hire Me
I focus on immediate clarity first, then durable systems.
The goal is not just to diagnose what is wrong. It is to create early momentum, reduce obvious pain, and leave behind infrastructure that scales.
First 30 Days
- Audit escalation paths and severity definitions
- Identify where engineering time is being wasted
- Map actual workflows against intended workflows
- Surface reporting gaps and tool trust issues
- Recommend quick wins and structural fixes
Next 60 to 90 Days
- Redesign escalation frameworks where needed
- Improve routing, automation, and case handling logic
- Establish Support to Product and Engineering operating rhythms
- Create dashboards leaders can actually use
- Build systems that scale without depending on heroics
How I Think
A support organization is a system. I make that system clearer, faster, and more trustworthy.
I work best where symptoms are showing up everywhere, but the root issues live in governance, tooling, prioritization, or cross-functional friction.
Example Support Operating Flow
This is the level I aim to operate at: not just improving one queue or one form, but strengthening the full decision path from intake to escalation to learning.
Selected Systems
Support Systems Designed for Scale
Experience designing systems across enterprise SaaS, fintech, and high-volume support environments, including Adobe and Tipalti.
I focus on systems that improve decision quality, reduce avoidable escalations, and make support organizations more scalable.
Standardizing Escalation Severity Across Support and Engineering
Business Outcome
Reduced escalation ambiguity and improved Support–Engineering alignment by introducing a shared, objective severity framework.
Challenge
Severity definitions varied across teams, leading to inconsistent prioritization, internal friction, and unnecessary Engineering interruptions.
What I Designed
A weighted severity model based on customer impact, customer tier, users affected, and urgency. The model was embedded into workflows via a JavaScript-based calculator to ensure consistent application.
Impact
Shifted escalation decisions from subjective judgment to shared operational logic, improving prioritization and reducing unnecessary escalations.
Interactive example
Designing End-to-End Support Architecture and Integrations
Business Outcome
Reduced case volume and improved resolution efficiency by redesigning intake, routing, and system integrations across Support, Product, and Engineering.
Challenge
Heavy reliance on email intake, limited self-service success, and lack of integration between Zendesk, Salesforce, and JIRA created inefficiencies.
What I Designed
- Self-service portal and knowledge strategy
- Salesforce integration for account context
- JIRA integration for engineering workflows
- Skill-based and round-robin routing
Impact
Created a scalable support system with improved data quality, faster resolution times, and stronger cross-functional alignment.
Additional Systems
Redesigning Email Intake into Structured Case Updates
Outcome
Improved intake data quality and reduced resolution time by converting unstructured email submissions into structured updates tied to the original case.
Designed
- Hidden Zendesk form not visible in standard UI
- Dynamic autoresponder link tied to original case
- Automatic ticket ID population
- Structured intake without added user friction
Reducing Duplicate Tickets with Automated Case Consolidation
Outcome
Reduced backlog and improved resolution speed by consolidating multiple tickets into a single source of truth per issue.
Designed
- Email-based case matching
- API-based field mapping across tickets
- Internal note aggregation
- Conditional merge logic
Building Support Observability with Agent Performance Systems
Outcome
Enabled data-driven decision making by providing visibility into performance, backlog health, and defect patterns.
Designed
- First reply and resolution time tracking
- Backlog segmentation
- Agent productivity metrics
- Defect tracking and categorization
How I Work
Systems That Scale Support Operations
I am strongest in environments that need a high-leverage operator who can connect support pain, tooling decisions, and business priorities without getting lost in theory.
Systems-minded operator with deep support infrastructure experience
I design and operate support infrastructure inside enterprise SaaS environments — escalation systems, analytics, CRM architecture, and cross-functional workflows at scale.
My operating model is simple: observe reality, align stakeholders, embed systems, and measure outcomes. I focus on systems that improve decision quality, reduce avoidable escalations, and make support organizations more scalable.
Operator First
I have spent years inside real support environments, not just advising from the outside. I understand the friction because I have worked inside it.
Systems-Minded
I focus on repeatable infrastructure, not one-off fixes. The goal is to improve the system, not just the ticket.
Technical Enough to Implement
From Zendesk administration and analytics to JavaScript customization and workflow logic, I can translate strategy into execution.
Cross-Functional by Default
I work comfortably across Support, Product, Engineering, and Operations to create frameworks all sides can actually use.
Outcome-Driven
I care about measurable impact: clearer prioritization, healthier escalations, better reporting, and less wasted engineering time.
Built for Staff-Level Leverage
My strongest work lives in identifying the system behind the symptoms and creating structure without slowing the business down.
Testimonials
What People Say About Working With Me
“Jonathan’s ability to solve complex business issues by creatively utilizing technology was very impressive. He could cut through clutter, identify the root cause, and deliver thoughtful solutions.”
VP of Operations
“He brings a creativity to problem solving that I do not see enough of. He is patient with clients, strong in execution, and constantly sharpening his skills.”
CEO / CTO
“Jonathan developed reports using both JIRA and Zendesk that met complex requirements. He was responsive, insightful, and a quick learner. I highly recommend his system administration and reporting skills.”
Developer Tools Support Engineer, Adobe
Role Fit
I am strongest in roles where support complexity needs real systems ownership.
This positioning works especially well for high-growth SaaS teams that are too complex for basic administration, but not yet mature enough to have fully trusted support infrastructure.
Best-Fit Titles
- Staff Support Operations
- Senior Support Systems Engineer
- Support Operations Lead
- Senior Zendesk Administrator
- Support Infrastructure Engineer
Best-Fit Environments
- High-growth SaaS teams
- Multi-product support environments
- Enterprise and SMB support complexity
- Cross-functional escalation pressure
- Tooling maturity gaps
Best-Fit Engagement Models
- Staff-level full-time roles
- Strategic advisory engagements
- Support systems assessments
- Escalation framework redesign
- CRM and reporting architecture projects
Let’s Connect
When support complexity increases, stronger systems matter.
If you’re hiring for a Staff-level Support Operations role or exploring targeted advisory support, I’d be glad to talk through the challenges your team is facing and where I could add leverage.
Discuss a Staff Role Explore an Advisory Engagement