QA Engineer

Programmatic QAQA at Finalytics goes well beyond clicking through a UI. Our platform makes model-driven decisions, runs LLMs and agents that generate content and answer questions, and depends on data pipelines that feed those models every day — and all of it has to be tested programmatically.We're looking for an engineering-minded QA team contributor to help build quality across three areas: our core personalization features, our LLM and agentic capabilities, and the data that powers them. This is a coding role, embedded in the same repo and release flow as our engineers that will report directly to the CTO. You won't just find bugs — you'll build the automated tests, evals, and data checks that let a small team ship trustworthy AI every sprint.Our stack is Python/Django with a JavaScript personalization tag, backed by MySQL, Celery, BigQuery, and AWS.What You'll DoProgrammatic QA of Core FeaturesExtend our scenario test runner — a proprietary harness that captures real production personalization requests and replays them across environments, asserting on expected algorithms and content selection. Grow it into automated regression across every client.Write automated tests in Python with pytest across our tiers — unit, integration, and end-to-end.Build headless Playwright end-to-end tests to verify how personalized content and tracking render on real client pages.Harden the pre-deploy quality gate and pre-commit checks that block bad changes automatically.Testing & Standardizing LLMs and AgentsDesign evals for non-deterministic AI features — our conversational analytics assistant, AI content builders, and generative SEO — measuring correctness, grounding, and regression across prompt and model versions.Test the tool-calling and agentic layers — that function-calling loops pick the right tools and guardrails hold on adversarial input.Validate our agent/MCP interface — contract conformance, rate limiting, authorization, and safe failure.Help set our standards for shipping AI — catching hallucinations and drift, and benchmarking prompt/model changes before clients see them.Data Quality EngineeringBuild automated data-health checks that flag stale rollups, incomplete coverage, and broken aggregations before they hit a client dashboard.Validate data pipelines end-to-end — rollups, funnel/rate/financial ingestion, and BigQuery — with drift detection across environments.Guard model inputs so the signals our ML depends on stay accurate and complete.Reliability & PerformanceTrack platform performance — response times, JS load, and page speed — and help keep it fast.Stand up quality dashboards — uptime, coverage, data-health, and eval scores.Collaboration & Bug LifecycleWork in the codebase alongside engineers to diagnose issues across development, release, and deployment.Drive the bug lifecycle — reproduce, capture with a failing test, and verify the fix.What We're Looking For3+ years in QA/SDET or test automation with a code-first approach.Strong Python — you write clean test code and can read the app you're testing.pytest (preferred) and browser automation (Playwright or Selenium).API and contract testing experience.A genuine interest in testing AI — comfortable with non-determinism, evals, and prompts.Data-savvy — strong SQL, and the instinct to validate pipelines and reconcile data.Building automated quality gates into the deploy and release process.Nice to HaveTesting or evaluating LLM applications — evals, prompt regression, tool-calling agents, or MCP.Data or analytics QA — BigQuery or ETL/rollup validation.Django, MySQL, or Celery experience.Security testing with SAST/DAST tooling.Familiarity with machine learning.Financial industry, personalization, or CMS/marketing-platform experience.Familiarity with AWS.SaaS startup experience on a fast-moving, multi-tenant platform.Why FinalyticsFrontier work — help define what QA means for AI, agents, and data-driven personalization in finance.Direct impact — help shape how quality works across the platform, reporting straight to the CTO.Automation-first culture — your work is code, in the same repo and release flow as engineering.Remote-first, collaborative, low-ego team growing with a scaling fintech.