Senior Quality Assurance Engineer

Hiring: Senior QA Engineer (Manual + Automation, Playwright, Data/Scraping)Experience: 5–10+ years (Senior) Location: Remote / Hybrid Type: Full-timeAbout Us – is building the next-generation Marketing AI Operating System — a platform where autonomous AI agents plan, analyze, and execute campaigns across Google, Meta, LinkedIn, Amazon, Flipkart, Blinkit, and more.We’re not building another dashboard. We’re building an AI-native command center that marketers use to orchestrate, optimize, and automate campaigns in real time.As a Senior QA Engineer, you’ll own quality across critical systems: agent workflows, analytics correctness, scraping/data pipelines, integrations, and end-to-end reliability.Who This Role Is ForWe’re not looking for QA engineers who just “run test cases.” We want quality leaders who:Think in systems, not ticketsBreak products before customers do (and document it so it gets fixed fast)Build durable automation that teams trust (not flaky tests)Understand data correctness and edge cases in real-world SaaSUse AI tools (Claude, copilots, test-gen) to move faster without losing rigorPush for better observability, reproducibility, and release confidenceIf you’re the person people rely on when a release must not fail — you’ll thrive here.What You’ll OwnProduct & Platform QualityOwn QA for web apps built with Next.js, Node.js, PythonDefine and maintain test strategy: smoke, regression, E2E, integration, and release sign-offValidate UX, reliability, permissions/auth flows, and role-based accessEnsure analytics & metrics correctness (numbers must match reality)Automation (Playwright-First)Build and maintain Playwright automation at production scaleImprove test reliability: flakiness reduction, trace debugging, deterministic environmentsCreate reusable helpers for selectors, fixtures, auth states, test data, and environmentsRun tests in CI/CD with clean reporting and fast feedback loopsScraping / Data-Heavy QA (Core Requirement)Test workflows involving scraping, crawlers, proxies, anti-bot behavior, and large datasetsValidate data pipeline outputs: completeness, correctness, deduplication, drift detectionDesign tests for rate limits, retries, concurrency, timeouts, partial failuresBuild confidence in systems that run across many categories/locations/platformsCollaboration & LeadershipPartner with engineering/product from PRD → design → rolloutRaise quality standards with clear risk assessments, bug reports, and prioritizationPropose improvements to tooling, environments, and release processMentor junior QAs or help developers write better testable codeMust-Have Skills / Requirements5+ years in QA (manual + automation) for web productsStrong Playwright experience (TypeScript/JavaScript preferred)Experience testing scraping/data ingestion systems or automation that interacts with real websitesStrong debugging mindset: logs, traces, HAR, network inspection, console errorsAPI testing (REST), Postman or equivalent, plus ability to automate API checksSQL fundamentals (Postgres preferred): validating data integrity and outputsExperience with CI/CD test execution (GitHub Actions / GitLab / similar)Can design test plans independently and push them to executionBonus PointsExperience testing AI-driven systems (non-determinism, evaluation, regression safety)Experience with distributed jobs/queues (Queues, workers, cron pipelines)Experience with Dockerized environments and test environments/staging parityBuilding internal QA tools, test dashboards, or data validation harnessesExposure to ad-tech / marketing platforms / ecommerce analyticsWhat You’ll GetReal ownership of quality in a high-velocity AI startupFreedom to shape QA strategy (not just execute it)Competitive compensation + growth path to QA Lead / QA Automation LeadA team that values speed and engineering disciplineInterview Process (Fast. Real. No fluff.)You get one shot.20 minutes to prove what you’re capable of.You’ll be given a real product scenario (data-heavy + UI + integration), and asked to:Identify key risks, edge cases, and failure pointsDescribe your test strategy (manual + automation)Explain how you’d build Playwright coverage that is fast + non-flakyShow how you’d validate scraping/data correctness and pipeline stabilityDemonstrate how you use AI tools to accelerate your work without lowering qualityNo long rounds. No theory quizzes. If you show sharp thinking and ownership — we move fast.If you want to ensure quality in a product shaping the future of AI-powered marketing — apply now and join

Apply Now