GLOBAL SERVICE EXCELLENCE DIRECTOR — HARRISON.AI
Twice.
13 years scaling global support organizations from the ground up.
50+ engineers across three continents. 24/7 follow-the-sun coverage.
96% CSAT across 200+ enterprise engagements.
The systems, the teams, the governance — built to last.
5 min read
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Where the work was done
Every metric below represents a system I built, a team I led, or a problem I solved at enterprise scale.
Executive-level escalations eliminated through governance frameworks
Maintained across 200+ enterprise engagements across three continents
From 3 to 50+ across US, EMEA, and APAC
Follow-the-sun support model with structured on-call rotations
Business unit turned around from $300K quarterly loss to profitability
Engineer ramp time cut from 3 months to 30 days
Support costs reduced while improving CSAT from 7.2 to 9.1
Services revenue scaled from $2.1M to $4.8M in 18 months
This isn't theoretical. I've designed and operated this model across three continents with 50+ engineers.
Live — coverage is always active somewhere
Every shift transition follows documented runbooks with explicit context transfer. No issue falls through the cracks between zones.
Shared observability, ticketing, and escalation systems mean every engineer in every zone sees the same picture.
Rotation schedules designed for sustainability — not burnout. Clear escalation tiers with defined response SLOs for every severity level.
Orientation before action. Validation before change. Proof points before promises.
FOCUS: Map the current support landscape, understand integration complexity, and build relationships with cross-functional partners.
KEY ACTIONS:
OUTCOME
A clear, evidence-based assessment shared with the CEO, with a recommended operating model direction grounded in observation rather than assumptions.
FOCUS: Translate observations into an aligned operating model and begin standing up foundational capabilities.
KEY ACTIONS:
OUTCOME
Shared alignment on the operating model, initial coverage in place, and a clear roadmap for scaling across all three customer groups.
FOCUS: Demonstrate the model works through measurable results while establishing patterns that scale.
KEY ACTIONS:
OUTCOME
Measurable SLO adherence, reduced escalation volume, and a service function stakeholders view as a reliable asset.
The same playbook applied across different companies, different scales, different industries — and it worked every time.
When I joined LogicMonitor, professional services was a three-person team. Over seven years, I built it into a 50+ engineer organization spanning the US, EMEA, and APAC with 24/7 follow-the-sun coverage.
The work included designing on-call rotations, escalation frameworks, capacity planning systems, and the automation that made it all scale without scaling headcount at the same rate. Executive-level customer escalations dropped by 75%. Services revenue grew 128%.
This is the closest analog to what Harrison.ai needs — standing up a global service function from first principles with real budget and executive sponsorship.
Harrison.ai Relevance
Greenfield build of global 24/7 support organization — same mandate, same scope
Joined during a turbulent post-acquisition period. The PS business unit was losing $300K per quarter. Within my tenure, I turned it to 42% gross margin, scaled the team from 8 to 22 across three regions, and established the delivery governance (PRRs, blameless postmortems, standardized SOWs) that made outcomes predictable instead of heroic.
The lesson: you can build fast if you build the right foundations first. Process before speed. Governance before scale.
Harrison.ai Relevance
Building process-first in a fast-moving environment — same tension between speed and governance
Leading engineering operations and services for a platform processing 5M+ monthly transactions. Reduced support costs by 85% while improving CSAT from 7.2 to 9.1. Designed incident response and escalation workflows. Currently serving as executive advisor on operational maturity and platform strategy.
The pattern holds: build the systems, measure what matters, automate what repeats.
Harrison.ai Relevance
Service operations at scale with direct CSAT accountability — same metrics orientation
Support is where your product meets reality. The question isn't whether to invest in it — it's whether to build it as a cost center or a competitive advantage. I've always chosen the latter.
Companies building 24/7 coverage for the first time underestimate the operational complexity of time-zone handoffs. Without structured runbooks, shared tooling, and clear escalation ownership, issues fall through during transitions. This is solvable with operating model design.
Products that integrate deeply into customer infrastructure — PACS, RIS, EHR systems in Harrison.ai's case — generate a long tail of integration-specific support issues. Without dedicated integration expertise, resolution times stretch and customer trust erodes.
Early-stage support organizations operate in break-fix mode without investing in infrastructure to prevent incidents. SLOs, error budgets, post-incident reviews, and ticket deflection strategies are easier to introduce early than to retrofit later.
"Build and lead a globally distributed engineering team"
Scaled from 3 to 50+ engineers across US, EMEA, and APAC over 7 years
"24/7 follow-the-sun coverage"
Designed and operated follow-the-sun model with structured on-call rotations and runbooks
"Own resolution speed — time-to-acknowledge, time-to-resolve, CSAT"
Maintained 96% CSAT across 200+ engagements; reduced escalations 75%
"Own the support technology stack"
Built automation frameworks reducing engineering effort 20%, accelerating delivery 40%
"Lead teleradiology integrations (PACS, RIS, DICOM)"
13 years of enterprise integration work; demonstrated ability to come up the curve quickly in unfamiliar domains
"Serve three customer groups equally well"
Simultaneously managed SaaS customers, partner ecosystem, and internal stakeholders with tailored service models
"Partner across the business"
Partnered with Sales, Product, Engineering, and Customer Success across every role
"Own major incidents — be the calm, accountable leader during Sev-1s"
ADHD-wired for high-pressure situations; built incident response and post-incident review practices
"Report to the CEO with evidence-based narratives"
Established executive reporting frameworks giving leadership predictable visibility into service health and risk
I want to be direct about two things.
I don't come from healthcare. I want to name that upfront rather than let it sit as an unspoken question. What I bring is 13 years of building the exact function described in this JD — across enterprise SaaS platforms where downtime had real consequences. Healthcare raises those stakes considerably, and I respect that. But the operational discipline transfers cleanly, and I have a track record of coming up the curve fast.
My brain is wired for this kind of work. I'm ADHD, and in a role like this, that's an operating advantage — not a footnote. I absorb new technical domains quickly and deeply. I naturally gravitate toward the details that matter in complex systems. And I'm at my best when things are on fire: Sev-1 incidents, organizational buildouts from scratch, the controlled chaos of creating something new under real pressure.
I have a young family. The idea that the systems I build could contribute to faster, more accurate diagnoses for people like them is not something I take lightly.
I'm ready to build this.
I've done the work of understanding Harrison.ai's challenge. If this framing aligns with how you're thinking about the role, I'd welcome the conversation.
