Private Equity Technology Leadership
I do not just lead teams. I lead outcomes. In Private Equity environments where time is capital and clarity is currency, I bring the execution mindset required to scale. I partner directly with PE advisors, operating partners, and executive leadership to align engineering velocity with business value.
I have led platform transformations that delivered 40% faster deployment cycles, 60% reduction in critical incidents, and $2M+ in cost optimizations through AI-powered automation. My teams consistently achieve 99.995% uptime while scaling to support 10x user growth.
I know how to operate under board scrutiny and deliver results that compound into measurable business impact.
Talk PE Strategy
What PE Firms Need from a Technology Leader
Execution Under Scrutiny
I operate under board-level scrutiny and investor pressure. I translate engineering complexity into clear business impact - the language PE advisors and operating partners need.
Measurable ROI
Every technology initiative I lead is tied to measurable business outcomes: deployment velocity, incident reduction, cost savings, uptime SLAs. No vanity metrics.
M&A Due Diligence
I conduct thorough technical due diligence on acquisition targets - assessing platform scalability, technical debt, team quality, and integration complexity before the deal closes.
Rapid Value Creation
PE timelines demand rapid value creation. I hit the ground running with proven frameworks for platform assessment, team evaluation, and 100-day transformation plans.
Transformation Outcomes
Real results delivered for PE portfolio companies under real-world constraints.
Faster Deployments
Reduced deployment cycles from 2 weeks to 3 days through AI-powered CI/CD optimization and automated testing workflows.
Uptime Achieved
SRE practices and intelligent monitoring that eliminated critical outages while scaling to 10x traffic growth.
Cost Savings
Infrastructure cost optimizations through cloud-native modernization and AI-driven resource management.
AI ROI Accountability
CFOs now demand tangible ROI from AI investments. I build the accountability frameworks that prove it - tracking cost-per-agent, automation ROI, and efficiency gains with the same rigor as infrastructure spend.
No AI theater. Measurable outcomes only.
- FinOps for Agents
I track AI agent costs the same way infrastructure costs are tracked: cost-per-workflow, cost-per-automation, ROI per agent deployment.
- Agent Reliability SLOs
Agents have SLOs just like microservices - uptime, accuracy, latency, and human escalation rates. Board-ready dashboards, not vague "AI adoption" slides.
- Engineering Velocity Metrics
DORA metrics, developer toil reduction percentages, and AI-assisted deployment rates - quantified, trended, and tied to business outcomes.
100-Day Transformation Framework
Diagnose (Days 1-30)
Comprehensive platform audit, team assessment, and technical debt quantification. I map the current state with precision - architecture risks, key-person dependencies, security gaps, and scalability constraints - without disrupting ongoing delivery.
Stabilize (Days 31-60)
Address the highest-risk findings from the diagnostic phase, establish platform health baselines, implement quick wins that demonstrate ROI, and build the operating cadence that will sustain the transformation through the acceleration phase.
Accelerate (Days 61-100)
Execute the first phase of the modernization roadmap, implement agentic AI tooling that delivers measurable toil reduction, establish board-ready reporting on engineering velocity and AI ROI, and position the platform for sustained value creation.
Technical Due Diligence Checklist
My due diligence assessments cover six critical dimensions that PE firms need to understand before closing a technology acquisition.
Platform Scalability
Architecture review for scalability constraints, load testing results, database bottlenecks, and the investment required to support 5-10x user growth.
Technical Debt Depth
Quantified technical debt assessment: how much investment is required to modernize, and what velocity tax is the debt imposing on the engineering team today.
Team Quality & Retention Risk
Engineering team capability assessment, key-person dependency mapping, attrition risk analysis, and culture evaluation for post-acquisition integration.
Security Posture
Security architecture review, vulnerability scanning results, compliance status (SOC 2, PCI, HIPAA), and identification of post-acquisition liability exposure.
Integration Complexity
Assessment of integration effort required to connect the acquisition with existing portfolio technology - APIs, data models, identity systems, and operational tooling.
AI Readiness
Assessment of whether the platform architecture can support agentic AI integrations - the key driver of engineering velocity gains in 2026 and beyond.