Jason Chaidez
Founder & Principal Engineer at Eigenvalue Systems. He scopes the work, builds the work, and is accountable for the work, with a background on both the finance side and the engineering side of the systems he now builds.
- Role
- Founder & Principal Engineer, Eigenvalue Systems
- Based
- Snohomish County, Washington
- Focus
- AI automation, data engineering, finance and control systems, internal applications
- Engagement
- Remote-first from the US; written scope and pricing before the build
Background
Jason's path runs through both sides of the systems he now builds. Years inside finance and accounting operations, across public accounting, property and multi-entity management, nonprofits, insurance, real estate, and operating companies, meant living with the work as it actually happens: the exports, the reconciliations, the approvals, the month-end that depends on one person remembering.
Today he builds automations, internal tools, and financial and quantitative models inside aerospace, alongside independent work through Eigenvalue Systems. That combination is the point: systems designed by someone who has been accountable for the numbers they produce, and who knows what an auditor, an operator, or a controller will ask of them later.
Principal disciplines
- AI automationControlled AI systems with evaluation, review, and traceable output
- Operational automationMonitored workflows with retries, exceptions, and audit records
- Data engineeringPipelines, models, and reporting that reconcile to source
- Finance and control systemsReconciliation, close, receivables, and auditability
- ERP and accounting integrationSystems that stay aligned with control totals
- Document intelligenceOCR and extraction with validation and human review
- Internal applicationsReview tools and portals built for the actual workflow
- Quantitative and financial modelingForecasting, scenarios, and model validation
Selected public work
Public project pages state their status and evidence level plainly. Work described as representative capability is exactly that, and internal or employer systems are described only at a level that exposes no organization, program, or data.
- Financial Operations Platform
- Accounts Receivable and Collections Automation
- System Integration and Migration Validation
- Quantitative Forecasting and Scenario Engine
- Document Intelligence and Controlled Extraction
- Controlled AI Assistant and Engineering Foundry
How the work is run
Every engagement starts by mapping the real operation: the data, exceptions, approvals, and failure points. Then the control boundary is defined, meaning what can be automated, what needs a person, and what evidence must remain. Implementation is tested against source truth, and handover includes the source, documentation, and operating knowledge needed to run the system without dependency on the author. Ownership and licensing are defined in writing for each engagement. The company principles behind that approach are described on the About page.
Working with Jason
The first conversation is about whether there is a bounded problem worth solving. Bring the process, the systems involved, and where the handoff breaks. An NDA is welcome before any sensitive detail is shared, and confidential work is treated as confidential by default.