Quality Architect
$146,200–$146,200 year
On-siteSalt Lake City, Utah, United States
Job Summary
Design enterprise end-to-end testing architecture and standards that support multi-system, cross-domain scenarios across CHG's integrated landscape. Define data quality standards for test datasets and maintain centralized test data catalogs to ensure AI-generated scenarios have the fidelity needed for trustworthy results. Evaluate and recommend quality tooling with a bias toward AI-assisted test generation and autonomous execution pipelines, while actively shaping how LLMs and agentic runners apply to quality solutions. Engage cross-functional teams to design test data pipelines for autonomous regression, partner with platform engineering on CI/CD integration, and advocate for testability as a first-class design concern. Represent the E2E testing practice in architecture reviews, security councils, and release readiness discussions to enforce load testing standards and ensure data integrity throughout downstream handoffs.
Required Qualifications
- 7+ years in software engineering, data engineering, or quality engineering
- at least 3 years focused on quality management or data architecture in enterprise environments
- Demonstrated experience designing testing solutions across complex, multi-system integrations
- Hands-on experience with relational databases, APIs, and data provisioning in CI/CD contexts
- Demonstrated experience designing synthetic test data pipelines for environments where production data cannot be used directly
- Security engineering awareness - understands access controls, audit requirements, and data identification in non-production systems
- Experience engaging architecture, platform engineering, or security teams as a technical peer and collaborator
- Familiarity with AI and automation tooling in a quality engineering or data engineering context
- Ability to influence technical direction across teams without direct authority - through standards, architecture, and credibility
- Ability to communicate quality technical architecture decisions to diverse audiences through documentation, and standards that teams can act on
- Define and maintain an enterprise testing roadmap
- Evaluate and recommend quality tooling and platforms, with a bias toward solutions that integrate with AI-assisted test generation and autonomous execution pipelines
- Define data quality standards for test datasets - referential integrity, coverage requirements, and edge-case representation
- Actively shape how AI capabilities are applied to quality solutions: LLM-assisted scenario generation from structured workflow inputs, agentic test runners, and AI-synthesized execution reporting
- Stay current on tooling relevant to quality engineering, autonomous test execution, intelligent defect categorization, observability integrations
- Work with cross functional teams to design test data pipelines that support autonomous regression execution
- Design AI-augmented quality intelligence: ensuring the quality architecture supports defect pattern analysis, risk flagging, and release readiness recommendations
- Engage the enterprise architecture team, bring quality architecture into system design conversations early, and advocate for testability as a first-class design concern
- Build and maintain data visibility across CHG's cross-system business workflows enabling test validation to trace a record from the source system through every downstream handoff and confirm data integrity at each point
- Maintain the impact assessment process when the source system schemas change and ensure test data catalogs and integration scenarios remain valid
- Partner with the platform engineering team on environment architecture, CI/CD pipeline integration, and infrastructure provisioning for testing at scale
- Develop and publish quality standards, reusable patterns, and self-service provisioning capabilities that teams across CHG can adopt consistently
- Build and maintain centralized test data catalogs that reduce manual data setup and accelerate coverage for new integration scenarios
- Represent the E2E testing practice in cross-functional forums: architecture reviews, platform planning sessions, security councils, and release readiness discussions
- Define and enforce load testing standards across the organization
- Must be available for weekend shifts
- Must be able to lift 50 lbs
Desired Qualifications
- Familiarity with Salesforce, Workday, or enterprise SaaS platforms as testing targets
- Experience with LLM-assisted test generation, agentic test execution, or AI-augmented quality intelligence tooling
- Background in microservices, event-driven architecture, or API-layer integration testing
- Experience working in an agile, squad-based engineering model
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