Experience: 3.00 + years
Confidential (based on experience)
Shift : (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type : Hybrid ()
Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Pet Health and Wellness Company)
(*Note: This is a requirement for one of Uplers' client - Pet Health and Wellness Company)
LLM, WCAG, AI testing, Cypress, Playwright, QA, Selenium
Pet Health and Wellness Company is Looking for:
QA Tester
Years of Experience : 3-5 years in software QA
Reports to : Operations Manager
A pod of 2 QA juniors, hired by you in sequence over your first two quarters
We ship a multi-tenant AI-native SaaS and an internal operating system at speed, with an Engineering Manager and a bench of junior developers. You are that gate — and nothing reaches a client or the wider team without passing a standard you own and can defend in writing.
You own the release criteria, the defect taxonomy and triage process, the usability standard, accessibility conformance, the evaluation harness for AI and agent features, and your pod of QA juniors.
Three things make this role harder than conventional QA, and they are the reason it sits in the senior pack:
Much of what we ship is non-deterministic. An AI agent given the same input twice may produce two different outputs, both defensible, one wrong. Testing alone cannot get you to a high quality bar. Inspection and static analysis remove roughly twice the proportion of defects that any form of testing does. So inspection and static analysis are the primary removal mechanism here and testing is the backstop — which means part of your job is arguing for review discipline when someone proposes skipping it to 'just test it harder.'
What you do not own: the build — architecture, implementation, stack, refactors the roadmap or sprint planning (you gate what is built, you do not choose it) infrastructure and environments and the junior developers themselves. The commonest failure mode for a first-time QA lead is drifting into unofficial project management because they are the person who notices everything. Author and version the definition of done, and ratify it with the Engineering Manager — ratified means they have read it, disagreed where they disagree, and the disagreements are resolved or escalated. Run the release gate as a checklist, not a judgement call — anyone should be able to run it and reach your answer
Severity is technical impact and is assigned by QA it is not negotiable by the person who wrote the code. Get static analysis into the pipeline and formal code inspection onto the calendar, with findings treated as gate items rather than advisory noise
Own WCAG 2.2 Level AA conformance: automated scan in the pipeline, manual keyboard traversal of changed flows, and a screen-reader pass
Build and maintain the AI evaluation harness — eval sets, graders, baselines, case-level regression diffs on every prompt change
Hire,



onboard and develop two QA juniors, and publish a quarterly quality report the rest of the business can act on
Agentic AI in Your Day-to-Day
This role is unusual in the pack: agents are both a tool you run and the thing you are testing. Static analysis triage — Agent clusters pipeline findings by root cause and separates gate-blocking items from noise before you open the report
This is the biggest single lever you have on regression and cross-browser coverage, and the one we most want you building out
Accessibility scanning — Agent runs the automated layer on every change and maintains the per-surface conformance statement and remediation backlog
Transcript triage for AI features — Agent surfaces the transcripts worth your human hour from the thousands you cannot read
Exploratory charter prep — Agent assembles the recent-change surface area so your time-boxed exploratory sessions start where the risk actually moved
Quality reporting — Agent assembles the defect distribution, gate outcomes and eval pass rates. The number that decides whether a release ships is yours, and an agent's suggested severity is an input to it, never a substitute.
An unaligned LLM judge is a random number generator with good manners. Before you trust one, you label a sample by hand, run the judge against it, and measure precision and recall — not raw accuracy, which an always-pass judge games trivially.
Scores tell you whether the graders fired only transcripts tell you whether they measure the thing that matters. When we lack data, you say 'we do not have enough data yet.' You are not a user of AI tools. You are the person who decides whether the AI we ship is actually working, and can show the method behind the answer.
Start at 20-50 cases drawn from real observed failures, covering four classes deliberately: happy path, edge cases, adversarial inputs, and off-topic requests the agent should decline cleanly rather
Versioned in the repository, never edited in a production console, and every prompt change triggers a full eval run before merge, diffed case by case against the recorded baseline. Offline and online. Offline evals gate deployment online evaluation watches live traffic for failure classes nobody anticipated. Online is where next quarter's cases come from.
3-5 years in software QA on a product, with real ownership of release readiness rather than test execution handed to you

- Holds severity and priority apart instinctively, and knows which of the two belongs to QA
- Functional, regression, smoke and exploratory testing on web,



with API testing (Postman or equivalent) and SQL for data verification
- Browser automation, and an appetite for driving it with agents. Hands-on with Playwright, Cypress, Selenium or equivalent, with cases versioned alongside the code they test. Static analysis and code-review discipline treated as first-class quality mechanisms, not as somebody else's process
- A candidate who has never had an escape has either not shipped or is not telling us the truth
- Writing that other people act on without asking a follow-up question. Calibrated about AI testing: you need not have built an eval harness, but you must recognise that one passing run proves almost nothing and one failing run proves almost nothing either, and your instinct must be toward repeated trials

Hands-on evaluation of LLM or agent features — eval sets, LLM-as-judge, prompt regression suites
x accessibility testing with manual keyboard and screen-reader passes, not scanner output alone
Agentic browser tooling in anger — Playwright MCP, browser-use, computer-use agents or similar — including an honest account of where it wasted your time
Not required: a formal QA certification
~ prior 'QA Lead' title — we care about whether you owned the gate, not what the box said.

Takes ownership — treats the role as their own operation ships the work end-to-end
Proactive — sees the next move before being asked ships the fix and reports
Performs under stress — triages and ships in real-time when things break
Calibrated about AI — neither dismissive of it nor uncritically enthusiastic knows where it works and where it does not
Code inspection and static analysis run on every change. Severity is set by QA and is not argued down. AI testing is set up properly. One QA junior is hired and running the release checklist unsupervised, and you can point to what they caught.
Intro call (30 min) — mutual fit and role expectations. We give you the compensation band in this call.
Team + culture conversation (45 min) — with the Operations Manager and the team you would work with
Direct report to the Operations Manager
Growth path: the quality function scales under you — your pod, your standard, and ownership of the AI evaluation harness as the product surface grows
Monthly KPI bonus structure (paid monthly, on outcomes) + promotion ladder
asserting exact-output assertions on AI output, or 'it worked when I tried it' reasoning
drifting into project management because you are the person who notices everything.
Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. So, if you are ready for a new challenge, a great work environment, and an prospect to take your career to the next level, don't hesitate to apply today.

📌 QA Lead Engineer - Hybrid (Nashik)
🏢 Uplers
📍 Nashik