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Chief Information Technology OfficerValuence-AI • Virginia, Minnesota, United States
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Chief Information Technology Officer

Valuence-AI
  • US
    Virginia, Minnesota, United States
  • US
    Virginia, Minnesota, United States
Apply Now

About

Chief Technology Officer (CTO) Valuence-AI Location: Hybrid / Remote (U.S. REQUIRED)
THIS IS NOT A C2C OPPORTUNITY
Reports to: Founder & CEO
About Valuence-AI Valuence-AI is building the first
Explainable Valuation Intelligence (EVI™)
platform for institutional decision-makers. We combine structured financial logic, regulatory-ready reasoning, and adaptive machine learning to produce defensible, reviewable valuations — not black-box outputs.
Our system doesn’t provide false confidence. It explicitly communicates what it knows, what it doesn’t know, and how it reached its conclusions. Every valuation includes assumptions, logic chains, and traceable reasoning — making mistakes correctable and governance-ready.
We are integrating directly into Loan Origination Systems (LOS) and enterprise workflows to become core infrastructure for valuation governance.
We are now hiring a
foundational CTO
to architect and scale the next generation of neuro-symbolic valuation intelligence.
The Role This is not a maintenance CTO role. This is an architecture role.
You will design and lead the development of a
neuro-symbolic AI platform
that combines:
Neural networks for pattern recognition and probabilistic inference
Symbolic reasoning engines for structured financial logic
Constraint-based systems for regulatory compliance
Explainability frameworks that make reasoning auditable
Your mandate: Build AI that institutions can defend in court, in audit, and in front of regulators.
Core Responsibilities 1. Architect Neuro-Symbolic Intelligence
Design hybrid AI systems combining neural networks with symbolic reasoning engines.
Implement rule-based financial logic integrated with probabilistic ML outputs.
Build constraint-aware inference systems that respect regulatory boundaries.
Develop structured reasoning graphs for explainable outputs.
2. Build the EVI™ Core Engine
Create assumption-aware valuation pipelines.
Ensure outputs include traceable reasoning paths.
Develop uncertainty quantification frameworks.
Embed “known vs unknown” confidence signaling.
3. Lead Engineering & AI Strategy
Recruit and manage high-caliber ML and platform engineers.
Define system architecture for scale, security, and enterprise integration.
Oversee data infrastructure and model governance.
Establish AI audit and compliance protocols.
4. LOS & Enterprise Integration
Architect API-first infrastructure.
Ensure seamless integration into enterprise Loan Origination Systems.
Design secure, scalable deployment models (cloud + on-prem options).
Implement SOC2-aligned security standards.
5. Long-Term Technical Moat
Drive patentable infrastructure development.
Build proprietary reasoning pipelines.
Develop regulatory-ready explainability frameworks.
Create defensible AI architecture that cannot be easily replicated.
Required Qualifications
10+ years in software engineering, ML systems, or AI architecture.
Deep experience with:
Neural networks (PyTorch, TensorFlow, JAX, or similar)
Graph-based reasoning systems
Knowledge representation and symbolic AI
Probabilistic modeling
Experience building production-grade AI systems.
Strong understanding of uncertainty quantification and model validation.
Familiarity with explainability techniques (SHAP, LIME, causal modeling, etc.).
Experience scaling SaaS infrastructure.
Highly Preferred
Experience with neuro-symbolic AI or hybrid reasoning systems.
Background in fintech, proptech, valuation, or regulated industries.
Experience building audit-ready AI systems.
Knowledge of valuation methodologies (DCF, comparable sales, income approach, etc.).
Familiarity with governance and regulatory compliance frameworks.
What Success Looks Like (First 18 Months)
Launch Version 2 of the EVI™ neuro-symbolic engine.
Deploy LOS-integrated valuation workflows.
Establish model explainability standards for institutional adoption.
File at least 1–3 core architecture patents.
Build and lead a 5–10 person AI engineering team.
Deliver enterprise-grade scalability and security readiness.
Leadership Profile You are:
A systems thinker, not a feature builder.
Comfortable operating in ambiguity.
Obsessed with first-principles architecture.
Fluent in both deep learning and structured logic.
Motivated by building category-defining infrastructure.
You understand that explainability is not a checkbox — it is architecture.
Compensation
Competitive early-stage salary – 10% Equity + 10% Additional upon KPI’s met= 20% Equity
Base Salary once seed funding is decured is $150k, OTE $300,000.
Base by EOY 6 $410K – OTE $600K+
Meaningful founding-level equity
Performance-based milestone upside
Opportunity to define an entirely new AI category
Why This Matters Black-box AI cannot survive in regulated valuation environments. Institutions require systems that are:
Defensible
Reviewable
Correctable
Transparent
Valuence-AI is building the infrastructure layer for institutional valuation governance.
If you want to build AI that regulators trust, courts respect, and institutions depend on — this is your role.
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  • Virginia, Minnesota, United States

Languages

  • English
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