Chief Customer Officer · Field Engineering & PreSales · AI/ML & Enterprise GTM
J. Scott Stradley
I build and scale the operating layer of enterprise software — the technical revenue function that turns complex technology into CFO-level business cases at each company's inflection point.
- $1B+Deal value influenced
- +300%ARR growth (Evolven)
- >54%Of BigPanda ARR
- Top 1%Quota attainment
This is a general overview of my background — not tailored to any single role. My work spans Chief Customer Officer, Field Engineering and Forward-Deployed leadership, PreSales and Solutions, and Business Value. I'm open to conversations across any of these. What follows is the shape of how I operate.
Why now
The gap is the function, not the technology
AI and real-time data platforms have crossed the adoption threshold — but most GTM organizations still cannot translate technical capability into P&L outcomes a CFO will sign. The gap is not the technology. It is the function that builds the business case, runs the proof, and compounds value post-sale. I have built that layer across four platform generations — from mainframe-era data integration to AI-native infrastructure — and measured it on commercial outcomes every time.
Why me
Four platform generations, one discipline
Same discipline, successive platform generations. I build and scale the technical revenue function — PreSales, Customer Success, Field Engineering, and Business Value — that turns complex technology into measurable growth at each company's inflection point.
HiveMQ
Founding Chief Customer Officer
2025–present
Unified Solution Engineering, Customer Success, and Business Value Consulting under one executive P&L reporting to the CEO.
Evolven
VP Global Solutions
2021–2025
$6M → $24M ARR (+300% over 3 years); global team of 13 built from near zero.
BigPanda
Field CTO
2017–2021
$200K → ~$30M; anchored >54% of company ARR; authored the Command of the Message framework.
Informatica
Sr. Account Executive
Earlier career
MetLife flagship <$1M → >$15M ARR; $8M+ annual services quota; contributed to $300M+ annual license bookings.
What I bring
Proof-backed pillars
- 01
Build the function from zero
Designed and stood up global Solution Engineering, Customer Success, and Business Value organizations — hiring, process, and P&L accountability included.
- 02
Translate complexity for the C-suite
Authored business cases totaling $200M+ by hand. Turned technical proof points into CFO-ready narratives that close enterprise deals.
- 03
Deliver 2–3× growth
Evolven ARR +300% in three years. BigPanda from $200K to ~$30M. MetLife from <$1M to >$15M ARR. Pattern repeats.
- 04
Make technical work commercially accountable
Cut Demo-to-POC time 50% and POC duration 75% at Evolven. Every SE engagement tied to a value milestone, not an activity metric.
Fit
Why this role
If you're scaling an AI-native platform, the gap is rarely the technology — it's the function that turns it into a business case a CFO will sign, and the post-sale motion that compounds it. That's the layer I build: Solution Engineering, Customer Success, and Business Value under one roof, measured on outcomes. I've built it across four platform generations, most recently as a founding CCO.
Enterprise clients
Trusted at scale
- Enterprise data platform engagements
- grew <$1M to >$15M ARR
- Fortune 100 financial services
- Enterprise operational intelligence
- Global digital operations
- Regulated industry platform adoption
- Insurance technology modernization
- SaaS platform expansion
- Retail digital transformation
- Global banking technology
- Financial services infrastructure
- Enterprise platform partnerships
Discussion
Questions worth exploring
- 01
Where is your post-sale motion leaking expansion revenue right now?
- 02
Is your SE org measured on commercial outcomes, or on activity?
- 03
What would it take to tie every technical engagement to a value milestone?
- 04
Where does "AI-native" still lack a CFO-ready business case?
Close
Let's talk
I didn't write a cover letter. I built this — a working value tool, a business case, and a site that argues its own case. If you're building a customer organization that has to match the technology behind it, I'd value thirty minutes.