Senior Quality Engineer
Quick Summary
Why join us? We’re a global tech company, just not the kind you’re picturing. Sure, we’ve got catered lunches, team events, cool merch, and yes... dogs in the office. But that’s not why people join.
At SafetyCulture, we help businesses get better every day by giving front-line teams tools to capture issues, learn, and act — across web, mobile, and an evolving ecosystem of sensors, integrations, and AI-powered capabilities.
Quality Engineering is central to that mission. Our Quality Engineers enable teams to ship high-quality software fast and with confidence, by embedding quality into every phase of delivery and using automation and AI to make quality scalable across our platform.
As a Senior Quality Engineer, you are an enabler and multiplier for product and engineering teams:
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You help teams own the quality of their deliverables (self-serve quality) while ensuring we maintain a consistently high bar across the platform.
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You use data, automation, and AI tooling to surface risks, reduce toil, and improve the reliability and performance of our products.
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You work across the lifecycle — from discovery and design to deployment and production — to make sure quality is designed in, not tested on at the end.
You’ll be part of the central Quality Engineering team working across our engineering groups, collaborating with engineers, product managers, designers, and data/AI specialists.
In this role you will:
Raise the quality bar of our product by making quality expectations explicit, measurable, and aligned with group and business goals.
Shine a light on product quality by defining and maintaining metrics, dashboards, and scorecards that make quality visible and actionable for groups and leaders.
Improve efficiency through automation and AI by expanding automated testing, trialing AI-based testing tools, and removing manual, repetitive work from the delivery process.
Support building and testing at scale by contributing to load and performance testing in critical domains so we can confidently serve large, complex customers.
Strengthen a collaborative, knowledge-driven quality culture by sharing practices, mentoring others, and contributing to quality initiatives that benefit engineering as a whole.
Design quality capabilities (metrics, dashboards, automation, AI-assisted workflows) that scale across teams and reduce dependency on individual QE involvement over time.
We use a combination of human judgment, automation, and AI to scale quality:
Human-led: Defining quality strategy, risk assessment, and decision-making in ambiguous or high-impact scenarios
AI-assisted: Using AI to accelerate test creation, analysis, triage, and insight generation
AI-driven: Automating repeatable quality signals, checks, and workflows to enable teams to increasingly self-serve quality
Our goal is to progressively evolve from manual and QE-led activities toward more automated and AI-enabled systems, with QE focusing on designing, enabling, and governing these systems while continuing to apply hands-on support where needed.
You’ll work with our QE team and cross-functional groups responsible for key parts of our SaaS platform — from inspections and actions, to training, analytics, integrations, and platform capabilities. Each group has:
An Engineering Manager, Product Manager, and Designer
Direct access to customers and support teams
Support from specialists in Quality Engineering and Platform
Quality Engineers are centrally aligned to the QE team and work with multiple product groups, enabling us to share learnings, reusable assets, and consistent practices across SafetyCulture.
Partner with product and engineering to understand our current quality practices and maturity and co-create an improvement roadmap grounded in data.
Help define our quality strategy that align with industry best-practice, business goals, and quality goals and priorities.
Help identify gaps, risks, and opportunities for improvement in our approach to quality.
Contribute to test strategies and plans that cover unit, integration, API, UI/e2e tests, observability, and production validation.
Help design and maintain automated tests (API, integration, and critical end-to-end flows) that run in CI/CD and provide fast, reliable feedback.
Work with engineers teams to improve test reliability ensuring pipelines are trustworthy and fast.
Experiment with and adopt AI-enabled tools (e.g. for test generation, coverage analysis, bug triage, anomaly detection) where they demonstrably improve quality and efficiency.
Build reusable frameworks, dashboards, templates, and AI agents that make quality increasingly self-serve for product teams.
Define and evolve quality metrics (e.g. CPRs, bug age and backlog, incident trends, crash rates, performance indicators) and connect them to team goals.
Build or extend dashboards and automated reports that provide timely, continuous feedback on product health to groups and stakeholders (e.g. Slack updates, Grafana dashboards, scorecards).
Use metrics and customer feedback to prioritise quality work (CPRs, bugs, tech debt, incident improvement actions) and drive remediation in the most impacted areas.
Ensure quality signals are consumable directly by engineering teams and leaders, enabling action without requiring QE interpretation or intervention in most cases.
Help define and validate performance limits and SLOs and ensure quality checks are integrated into delivery workflows.
Ensure quality practices support the needs of enterprise customers (scale, reliability, data integrity) and complex organisational setups.
Contribute to performance and load testing for critical workflows and services, in partnership with platform and product teams.
Share knowledge through workshops, pairing, coaching, and documentation, helping engineers and product managers build confidence in quality practices and tools.
Lead QE working groups and cross-team initiatives to drive horizontal improvements (e.g. mobile parity, test device strategy, incident processes, API frameworks).
Contribute to the broader engineering community via internal talks, roadshows, newsletters, or external content, aligning with QE’s role as a thought leader in quality.
You will be a great fit if you have:
Experience in software quality or engineering roles, with a focus on building and testing modern web, mobile applications and services.
Strong hands-on skills with test automation frameworks and tools, especially for APIs and end-to-end flows, and a solid understanding of good unit/integration testing practices.
Experience working with microservices, distributed systems, and cloud-hosted SaaS, including both manual and automated validation approaches.
Familiarity with or strong interest in using AI-powered tools to improve testing, triage, or quality analysis (even if you haven’t used them extensively yet).
Demonstrated ability to lead quality improvement initiatives end-to-end — from discovery and planning, through execution, stakeholder communication, and measuring outcomes.
Understanding of how testing and quality practices interact with CI/CD pipelines and modern delivery practices.
Strong communication, collaboration, and influencing skills — you can work effectively with engineers, engineering managers, product managers, designers, and stakeholders across groups.
A growth mindset and comfort working in a fast-paced, evolving environment where priorities can shift and learning is continuous.
Prior experience in Agile delivery environments and cross-functional product teams.
Success in this role is demonstrated not only by improved quality outcomes, but by the extent to which teams can independently assess risk, quality, and readiness using systems and signals designed by QE.
Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
Experience with at least one modern programming language (e.g. Golang, JavaScript/TypeScript) and willingness to dig into code when needed.
Exposure to non-functional testing (load, performance, resilience, reliability) and observability practices.
Experience working with AI features or AI-assisted workflows (e.g. AI testing tools, anomaly detection, intelligent triage), and an interest in responsible and ethical AI practices.
Background in platform or infrastructure quality, particularly in high-scale, multi-tenant SaaS environments.
If you’re passionate about helping teams move fast with confidence, excited by the idea of using data, automation, and AI to improve quality, and want to shape how a mission-critical platform is built and operated, we’d love to hear from you.
Location & Eligibility
Listing Details
- Posted
- July 23, 2026
- First seen
- July 23, 2026
- Last seen
- July 23, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 62%
- Scored at
- July 23, 2026
Signal breakdown
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