Product Quality Engineer

Product Quality Engineer — AI-Powered Bug Hunter & Fixer

The Role

This isn't traditional QA, and it isn't a junior engineering role—it's both, supercharged with AI. As our Product Quality Engineer, you'll be the guardian of product excellence , hunting down bugs, understanding their impact, and fixing the majority of them yourself using AI-assisted development tools. You'll be the person who makes sure our product feels polished and reliable.

You'll work at the intersection of product, engineering, and customer success—deeply understanding user workflows, catching issues before they escalate, and either shipping fixes autonomously or writing crystal-clear bug reports for senior engineers when issues are complex.

What You'll Actually Do60% — Hunt, Fix & Ship (Autonomous Bug Resolution)

• Own small-to-medium bugs: Buttons not visible, weird scrolling behavior, filters not applying, broken links, styling issues, minor validation errors—you fix these directly using AI coding tools (Cursor, Claude Code, v0, etc.)
• Read the codebase: Navigate our React, Python/FastAPI, and infrastructure code to understand where bugs originate
• Write clean fixes: Make targeted changes, test thoroughly, commit with clear descriptions, and ship via PR
• Leverage AI effectively: Use LLM-powered tools to understand unfamiliar code, generate fixes, write tests, and debug—you're comfortable with AI as your pair programmer
• Test end-to-end: Verify fixes work across browsers, mobile, different user roles, and edge cases before merging

25% — Triage & Escalate (Classic QA for Complex Issues)

• Identify complexity: Recognize when a bug touches multiple systems, requires architectural changes, or is P0/P1 severity
• Write exceptional bug reports: Create detailed tickets with clear reproduction steps, expected vs. actual behavior, screenshots/videos, user impact assessment, and initial diagnosis
• Prioritize ruthlessly: Help engineering and product understand what's urgent vs. what can wait
• Track to resolution: Follow escalated bugs through to deployment, verify fixes, and close the loop

10% — Quality Systems & Prevention

• Build quality muscle memory: Document common bug patterns, create checklists for new features, suggest process improvements
• Expand test coverage: Write automated tests (unit, integration, E2E) for frequently broken areas
• Monitor production: Set up alerts for error spikes, track user-reported issues, identify quality trends

5% — Cross-functional Collaboration

• Partner with Customer Success: Be the first responder when customers report issues; translate vague complaints into actionable bug reports
• Work with Product: Provide feedback on new features from a quality lens during design and beta testing
• Support Engineering: Jump into Slack threads to help debug production issues or validate fixes

What Makes You a Great FitMust-Haves

• 2-4 years in QA, support engineering, or junior dev roles where you got close to the code
• AI-native developer workflow: You already use Cursor, Claude Code, GitHub Copilot, or v0 regularly and know how to prompt effectively for code generation and debugging
• Light full-stack coding ability: Frontend: Can read and modify React/TypeScript, understand HTML/CSS, debug in browser DevTools
• Backend: Can read Python (FastAPI/Django), understand API requests, follow control flow
• You don't need to architect systems, but you can find and fix bugs in existing code
• Debugging tenacity: You love the detective work of figuring out why something broke
• Git basics: Comfortable with branches, commits, PRs, and code review workflows
• Product intuition: You understand what makes software feel broken vs. just different; you care about user experience deeply
• Communication clarity: Can explain technical issues to non-technical teammates and vice versa

Nice-to-Haves

• Experience with test automation frameworks (Playwright, Cypress, pytest)
• Background in customer support or success roles with technical depth
• Exposure to cloud infrastructure (GCP/AWS), monitoring tools (Sentry, Datadog), or CI/CD pipelines
• Familiarity with SaaS analytics products , dashboards, or data visualization
• Prior work at fast-moving startups where you wore multiple hats

What Won't Work

• Need heavy mentorship or hand-holding on every task
• Uncomfortable with ambiguity or self-directed work
• Ego tied to writing new features vs. fixing existing ones
• Can't pivot between "I'll fix this" and "I need help" appropriately

Why This Role is Unique

You're an engineer — writing code, shipping PRs, deploying to production.

You're QA — testing rigorously, thinking about edge cases, advocating for quality.

You're product-minded — understanding user workflows, prioritizing impact, caring about polish.

You're AI-accelerated — using cutting-edge tools to punch above your weight technically.

This is a force multiplier role . Done well, you'll free up senior engineers to focus on architecture and features while you handle 60-70% of incoming bugs autonomously. You'll also become one of the people who knows our product most intimately.

Growth Path

This role is a launchpad:

• → Senior Product Quality Engineer: Lead quality systems, mentor others, own release quality
• → Software Engineer: Build features, graduate from fixes to new capabilities
• → Product Manager: Leverage deep product knowledge and user empathy
• → QA Engineering Lead: Build out testing infrastructure and automation strategy

Why Join Clarity

• Fully Remote: Work from anywhere with flexible core hours 🏠
• In-Person Meetups: Regular team gatherings and monthly virtual events 🎉
• Generous Time Off: Comprehensive vacation policy 🏝️
• Growth Budget: Continuous professional development support 📈
• Equity: Meaningful stock options in a fast-growing startup 💼
• Autonomy: Ship fixes yourself—no waiting for permission or eng time 🚀
• AI-Native: Use the latest coding AI tools; we'll support your learning 🤖
• Impact: Every bug you fix makes our customers' experience better immediately
  

About Clarity

Clarity is an AI-first startup revolutionizing how companies understand customer feedback. Our platform consolidates feedback from app reviews, support chats, surveys, and social media into actionable insights. Trusted by brands like Grubhub, OpenAI, Dropbox, Uber, and Careem, we help companies turn messy customer data into clear, actionable intelligence.

We're backed by top investors including Neo, Sukna, Race Capital, Propeller, and Wamda, having raised $12M to date.