Principal Technology Architect - QA

Precisely US Jobs

9h•Remote

About The Position

Precisely is the leader in data integrity, empowering businesses to make more confident decisions based on trusted data. This role is for building the next generation of our SaaS platform, focusing on owning the quality architecture to ensure trustworthiness. As a Principal Technology Architect - QA, you will design systems, standards, and governance to elevate quality across all product segments. This is an AI-first organization, and the role involves integrating AI-driven testing, intelligent automation, and modern quality tooling into daily workflows. It's a hands-on architecture position where you will build test frameworks, design quality gates, set reliability targets, and create shared infrastructure. You will collaborate with engineering leadership to align quality strategy with business outcomes, mentor engineers, shape hiring practices for quality mindset, and grow technical leaders. The ideal candidate is excited about solving complex problems at scale, rethinking quality in a modern SaaS organization, and making lasting improvements.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Equivalent work experience is accepted in place of a degree.
15+ years of progressive experience in software quality engineering, test architecture, or related technical leadership roles, with demonstrated org-wide architecture leadership
Deep expertise in test automation frameworks, CI/CD pipeline design, quality gate implementation, and testing strategies for large-scale SaaS platforms.
Hands-on experience applying AI to quality workflows (e.g. AI-driven test generation, intelligent test selection, or automated defect detection)
Track record of driving adoption of technical standards across multiple teams or product areas, including working with leaders who do not report to you
Comfortable using generative AI tools (e.g. GitHub Copilot, Claude Code, or custom LLM integrations) to accelerate day-to-day quality workflows such as test generation, defect triage, and root-cause analysis.
Able to critically evaluate AI-generated outputs and set guardrails so that AI-produced test artifacts meet reliability, security, and compliance standards.
Experience evaluating and integrating AI-powered quality tools (e.g. autonomous testing platforms, AI-based test maintenance, predictive analytics for defect detection) into org-wide workflows.
Open to continuously adopting new AI capabilities as they emerge and excited to shape how the org integrates them into quality practices.

Nice To Haves

An advanced degree is a plus.
Experience defining and scaling quality practices across multiple product segments in a large SaaS or cloud-native organization.
Familiarity with contract testing, chaos engineering, or advanced reliability practices (SLOs/SLIs, error budgets).
Experience establishing quality centers of excellence or community-of-practice models across engineering organizations.
Exposure to security testing practices, compliance frameworks, or regulated industry quality standards.
Experience with observability and monitoring platforms (Datadog, Splunk, Grafana, PagerDuty) at an architectural level.
Track record of representing an organization externally through conference talks, published writing, or industry working groups in quality engineering.

Responsibilities

Set the quality architecture direction for the org: design quality gates, define reliability targets, and choose the testing infrastructure that all product segments build on.
Build and maintain a governance model for quality practices so that standards, processes, and tooling are adopted consistently across engineering teams.
Design and deliver scalable test automation frameworks that teams can adopt and extend to improve coverage, speed, and confidence in every release.
Bring AI into quality engineering: evaluate and roll out AI-driven test generation, intelligent test selection, defect prediction, and automated monitoring.
Own the performance and resilience strategy: set performance budgets, define monitoring standards, and create disaster recovery and incident response frameworks.
Partner with product and engineering leaders to balance release velocity with system health, making sure teams can ship fast without cutting corners on quality.
Evaluate and introduce new tools, patterns, and practices that keep our quality approach current as the platform and industry evolve.
Mentor engineers across teams, raise the bar on how we hire for quality mindset, and contribute to engineering maturity across the organization.
Represent Precisely externally as a thought leader in quality engineering through talks, writing, or industry engagement.