Lead Quality Engineer - AI Platform
TrialView is looking for a Lead Quality Engineer with 5 or more years of experience, to focus on our AI platform.
What we're looking for
TrialView builds AI-powered tools for litigation, case preparation, and evidence review. Our users are barristers, solicitors, and litigators - people whose tolerance for software error in front of a judge is zero. A mistagged document, a broken link in a court bundle, or a wrongly grounded AI output is not a cosmetic bug here; it is a professional risk for our customers.
At the same time, our engineers ship AI-assisted code at a pace traditional QA cannot match, and the product itself contains generative AI whose outputs are probabilistic. We are hiring the person who owns the quality systems that make that combination safe - someone who can scale quality faster than we scale code.
If that problem statement excites you rather than alarms you, keep reading.
The mission
You will own quality across the TrialView platform, focused first where the stakes are highest: the React frontend our users live in, and the court-facing artifacts they hand to judges. This is a hands-on lead role: you own the quality function, and you build the systems yourself. (Scope note: our AI research team owns model-output evaluation; you own the quality of everything users touch, including the experience of our AI features.)
You will not start from a blank page: a unit suite gates every deploy, alongside a Playwright e2e suite, strict TypeScript, and per-PR preview deployments - plus a layered programme now rolling out, spanning agentic UI verification, visual regression, production monitoring with session replay, and risk-based release certification.
We practise continuous delivery - small changes, daily releases to production, no release trains, no week-long manual regression marathons. If Accelerate or Continuous Delivery sits on your shelf, you will recognise the culture. Your job is not to manually inspect everything we ship; it is to own and harden the test harnesses that make daily releases safe, reserving expert human judgement for the highest-risk surface area.
What you'll do
- Own the release decision. Our gates let us ship daily; you own the criteria those gates enforce, and you personally arbitrate the releases that carry real risk - with the authority and the evidence to say “not yet.”
- Harden the frontend regression net (first 90 days). Make the e2e suite a true gate, extend it to the interaction-level defects that matter, own visual regression, and select our durable E2E tooling. Every bug that reaches production gets a regression test so it can never escape the same way twice.
- Own artifact correctness. Programmatically verify exported court bundles - links resolve, pagination correct, bookmarks survive. When a firm hands our output to a court, it must simply be right.
- Codify expert exploratory testing. Partner with our in-court evidence presenter, who exploratory-tests each release; turn what her judgement finds into automated coverage, so expertise compounds instead of evaporating.
- Lead and grow the quality team. You start with a junior QA engineer already in place - PR checks and automated coverage today - to coach and develop, and you hire the engineers who join as we scale, setting the standard they inherit.
- Table stakes: structured defect reports, maintained test documentation, proactive communication - and daily use of AI tooling to multiply your throughput, with healthy scepticism about AI-generated tests validating AI-generated code.
What you'll bring
- 5+ years in QA / quality engineering, spanning deep exploratory manual testing and strong automation.
- Proven depth in frontend quality: e2e suites (Playwright, Cypress, or similar) that catch interaction-level regressions, visual regression, and real-
browser verification - integrated into CI/CD. - Experience building quality gates and release processes for teams that ship continuously.
- Active use of AI tooling in your own QA work - we will ask how it has changed your practice in the last year.
- Ability to debug across the stack, excellent written communication, and high autonomy in a fully remote, high-accountability environment.
Our stack
React (strict TypeScript); C#/.NET APIs; Python AI pipelines; Azure Functions,Storage Queues, Cosmos DB. Direct experience is a plus, not a requirement - we care that you can learn a system quickly and find where it breaks.
Nice to have
- distributed/asynchronous systems testing
- document or PDF pipeline testing
- experience testing AI/LLM-driven features or familiarity with evaluation concepts
- legaltech, regulated-industry, or high-stakes SaaS background.
Who will succeed
- A systems thinker who would rather eliminate a class of bugs than file ten instances of it.
- Someone with the backbone to say “we should not ship this yet” - and the evidence to back it up.
- A pragmatist who balances automation, AI tooling, and human judgement based on risk, not habit.
What we offer
- Genuine ownership of quality - including the release decision itself - in a foundational role that will shape our engineering culture as we grow.
- Fully remote, high autonomy, direct access to the CTO and senior engineers.
- Compensation benchmarked to market rate for senior talent in your location - specifics shared in the first conversation.
How to apply
Send your CV to jobs@trialview.com with a short note on one of: the hardest non-deterministic or AI-driven system you have tested and how you approached it, or how AI tooling has changed your QA practice in the past year. We read every application.