Quality Engineer AI First

Verdantis; Mumbai; In loco; INR 600.000 - 1.000.000; Tempo pieno

Descrizione del lavoro

Verdantis is seeking an early-career AI-first quality engineer to test the AI-native MRO360 platform and MDM product used by large plants. You will craft AI-generated test cases, build AI-enabled automation, and explore edge cases across UI, API, and data behaviors.

Ideal candidates have 1–3 years of software testing or development experience, daily AI tool usage, and a willingness to learn domain concepts like material master data and reorder points. Based in Mumbai or willing to relocate.

Competenze

• Has 1–3 years in software testing or development or strong Fresher with projects.
• Fluent with AI tools, can show test suite generation and refinement with an LLM.
• Knows boundary, equivalence, negative paths, and data test design; explains AI test quality.

Mansioni

• Own test coverage for new features across MRO360 and MDM; generate AI-based test cases and execute before sprint end.
• Test AI behavior (stock levels, duplicate detection, classification) with PM and data scientists; track release accuracy.
• Reproduce customer defects with realistic data; write clear repros for developers and verify fixes.
• Build and maintain automated regression suites (API and UI) that run on every build.
• Run integration tests for SAP-style data flows; ensure error handling and idempotent re-runs.
• Assess security/IT needs: RBAC, multi-tenant isolation, performance at 200K+ SKUs, audit logs.
• Maintain living docs on AI tools/prompts for testing; share with engineering for better test design.
• Prepare one-page release readiness notes for Eng Lead and Delivery Head.
• Push back on shipping when evidence indicates risk; ensure product quality.

Conoscenze

AI testing

SQL

Test design

Automation

CI pipelines

Formazione

Bachelor's degree in Computer Science

Strumenti

Copilot

Claude

GitHub Actions

Descrizione del lavoro

You will be the first AI-first quality engineer at Verdantis, testing an AI-native platform MRO360 and our MDM product that large plants in energy, manufacturing and mining use to run their spare parts, equipment and material master data. The product makes decisions, not just screens: it recommends stock levels, flags duplicate materials and classifies parts. Testing means testing both the software and the judgement.

We do not want a manual tester with a 400-row spreadsheet, nor a classic automation engineer maintaining brittle scripts. We want someone early in their career who already uses AI to generate test cases, write and repair automation, explore edge cases and read logs and who wants to find out how far that can go. You will set the pattern for how quality is done here.

What you do

Functional testing

• Own test coverage for new features across MRO360 and MDM: read the story, generate the test cases with AI, prune and sharpen them yourself, and execute them before the sprint closes.
• Test the AI behavior, not just the UI: build evaluation sets for recommendations (stock levels, duplicate detection, classification), define what "correct" means with the product manager and data scientists, and track accuracy release over release.
• Reproduce customer-reported defects with real-shaped data (SAP material master, equipment, BOM extracts), write them up so a developer can fix them in one pass, and verify the fix.

Platform testing

• Build and maintain automated regression suites (API and UI) written with AI, reviewed and owned by you that run on every build.
• Run integration tests against SAP-style data flows: flat-file loads, OData/IDoc payloads, error handling, idempotency on re-runs.
• Test what enterprise customers' security and IT teams will ask about: role-based access, multi-tenant data isolation, performance at 200K+ SKUs, audit logs.

Raising the bar

• Keep a living record of which AI tools and prompts work for which testing tasks and share it with engineering, so test generation becomes part of how developers work.
• Report release readiness in one page the Engineering Lead and the Delivery Head can act on: what was tested, what was not, what is risky.
• Push back on shipping when the evidence says no.

What we are looking for

• 1-3 years in software testing or development, or a strong fresher with projects that show it. Attitude and tooling fluency matter more than years.
• Uses AI tools daily and can show it: a test suite generated and refined with an LLM, an automation script debugged with Copilot or Claude, a prompt library built for test design. We will ask for a live demonstration.
• Knows the basics of good testing: boundary cases, equivalence classes, negative paths, test data design and can explain why an AI-generated test case is weak.
• Comfortable with SQL for checking data loads and results against the database.
• Curious about the domain: willing to learn what a material master, a reorder point or an equipment BOM is, because the bugs that matter are domain bugs.
• Writes a clear defect report and a clear release note. Argues with evidence, not opinion.
• Based in or willing to relocate to Mumbai.

Nice to have

• Exposure to testing LLM-based features: prompt regression, evaluation datasets, hallucination and consistency checks.
• Experience with CI pipelines (GitHub Actions or similar) and running tests in them.
• Basic understanding of cloud deployments and multi-tenant SaaS.
• Any exposure to SAP, EAM or supply chain software is useful, not required.
• Performance or load testing with k6, JMeter or Locust.

Who this role is not for

• Someone who wants a test plan handed to them and executes it line by line.
• Someone who sees AI as a shortcut to avoid understanding the product. The tool generates; you are accountable.
• Someone who wants to stay in one layer. This role spans UI, API, data and model behaviour.
• Someone who is uncomfortable telling a senior developer their feature is not ready.