Why join us? Mitti by SafetyCulture is a global tech company, just not the kind you're picturing. Our almost 1,000-person team builds tools that make work better for the three billion frontline workers who keep the world moving. We've got big tech scale, without the sign-off layers or corporate theatre. This next chapter is about scaling smart, powered by AI, a clear vision and real ownership. Big tech impact, without the big tech ick. At Mitti, 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. The role As a Quality Engineer II, you are an enabler for product and engineering teams: • You help teams own the quality of their deliverables (self-serve quality) while ensuring we maintain a consistently high bar across the platform. • You use data, automation, and AI tooling to surface risks, reduce toil, and improve the reliability and performance of our products. • 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. How you can have an impact In this role you will: • Help 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 helping keep our products reliable and scalable for large, complex customers. • Strengthen a collaborative, knowledge-driven quality culture by sharing practices, and contributing to quality initiatives that benefit engineering as a whole. • Help design quality capabilities (metrics, dashboards, automation, AI-assisted workflows) that scale across teams and reduce dependency on individual QE involvement over time. How we approach quality 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. The teams 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 Mitti. What you’ll be doing Enable groups to own and improve quality • Partner with product and engineering to understand our current quality practices and maturity and contribute to an improvement roadmap grounded in data. • Contribute to our quality strategy and testing approaches 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. Embed quality early in the lifecycle • 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. Drive automation, AI usage, and tooling Proactively identify QE activities that should disappear into automation or agents over time, and track the reduction of manual effort as a measure of impact. Make quality visible through metrics and feedback • Define and evolve quality metrics (e.g. customer problem reports, 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 (customer problem reports, 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 interven