AI Governance Architecture Sprint
Design a practical governance layer for AI features without killing delivery speed.
You get: decision framework, SDLC control points, role ownership, implementation roadmap.
VP Engineering • AI & Compliance Operator
Ship AI-powered products faster — with audit-grade trust.
I help CTOs, CISOs, and founders build execution systems where product velocity and compliance reinforce each other.
HIPAA-ready operations
SOC 2 audit track
Operator-first execution
Engagements built for operators
Compliance Operating System Setup
Turn HIPAA/SOC 2/ISO/AI Act requirements into an execution model for engineering and operations.
You get: control map, evidence workflow, ownership matrix, audit-ready cadence.
Technical Due Diligence & Enterprise Readiness
Prepare product and process posture for enterprise buyers, security reviews, and scale pressure.
You get: gap report, risk-prioritized plan, remediation sequence, buyer-trust narrative.
Proof, not theory
Anonymized HealthTech Case
Compliance-by-design while scaling engineering delivery
Led engineering execution model design and operational rollout for a US health platform handling sensitive data across product and infrastructure teams.
- Successfully passed HIPAA audit
- Successfully passed SOC 2 audit
- Established repeatable cross-functional control workflow
Operator insights
Three patterns I see repeatedly in AI, engineering, and compliance work — and where teams usually burn time, trust, or both.
AI architecture fails when it ignores operating reality
Most teams do not lose on model quality. They lose on brittle orchestration, missing ownership, and workflows nobody can support under real delivery pressure.
Compliance becomes expensive when it lives outside execution
If controls sit in spreadsheets instead of delivery flow, evidence gets recreated by hand, engineers bypass the system, and every audit becomes a fire drill.
Enterprise trust is won before procurement starts
Buyers look for decision discipline, access boundaries, auditability, and remediation ownership — not polished security language pasted onto an unstable operating model.
About
I’m Yan Dyshkalps. I lead engineering with an operator mindset: turn ambiguity into execution, make systems hold under pressure, and build trust before the audit or buyer forces the issue.
My work sits where AI delivery, software operations, and compliance meet. I help teams design operating models that are fast enough for product reality and disciplined enough for regulated environments.
Tell me your bottleneck
I reply personally. If there’s no fit, I’ll still point you to the fastest next step.
Prefer LinkedIn? Message me there.