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Open nowPosted 20 hours ago

QA Engineer

Weekday AI

Where
Bengaluru, KA, India
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Your applicationOpen nowQA EngineerWeekday AI · Bengaluru, KA, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Weekday AI's own form.

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 20 hours ago

The posting

This role is for one of Weekday’s clients Salary range: Rs 1200000 - Rs 1600000 (ie INR 12 - 16 LPA)

Min Experience: 4+ years Location: Bengaluru, Karnataka, India JobType: full-time

We are looking for a skilled QA Engineer to join a data and AI-driven engagement in the pharma commercial space. You will be responsible for ensuring the quality, reliability, and AI-readiness of a modern application stack spanning React frontends and Python-based backend services — including AI/ML components.

Requirements

Key Responsibilities

  • Design, develop, and execute comprehensive test plans covering frontend applications built with React and backend systems using Python and REST APIs.
  • Build, maintain, and enhance automated test suites across UI, API, and integration layers.
  • Conduct AI readiness assessments by validating model inputs and outputs, data pipelines, edge cases, hallucination risks, and performance thresholds for AI-powered features.
  • Collaborate with data scientists and engineering teams to define acceptance criteria for machine learning models and AI algorithms.
  • Perform functional, regression, performance, and User Acceptance Testing (UAT) across development and release cycles.
  • Identify, document, track, and manage software defects while coordinating with development teams for resolution and retesting.
  • Integrate automated test cases into CI/CD pipelines and contribute to implementing quality gates.
  • Validate data accuracy and consistency across pharmaceutical commercial workflows, including sales force data, HCP/HCO information, and market access.
  • Participate in sprint planning, reviews, and other Agile ceremonies.
  • Provide QA sign-off and ensure product quality before production releases.

Required Skills and Experience

  • 4–6 years of hands-on experience in Quality Assurance and software testing within software product or analytics environments.
  • Strong experience testing React-based frontend applications, including component testing and end-to-end testing.
  • Proficiency in frontend automation tools such as Cypress, Playwright, or Selenium.
  • Strong backend and REST API testing experience using Python-based frameworks such as Pytest and Requests.
  • Exposure to testing AI/ML systems, including model validation, output consistency checks, data drift detection, and handling non-deterministic behaviour.
  • Familiarity with CI/CD tools such as GitHub Actions, Jenkins, or similar platforms, including automated test integration.
  • Solid understanding of test design techniques, including boundary value analysis, equivalence partitioning, and exploratory testing.
  • Strong documentation skills for preparing test cases, defect reports, test results, and QA sign-off summaries.

Good-to-Have Skills

  • Prior experience in the pharmaceutical commercial domain, with an understanding of HCP/HCO targeting, sales force effectiveness, market access, or promotional analytics.
  • Experience with performance and load testing tools such as Locust, JMeter, or k6.
  • Familiarity with MLflow, model registries, and AI observability tools.
  • Understanding of data quality frameworks and validation techniques for structured and unstructured data.
  • Exposure to AI/ML testing methodologies and quality assurance practices.

Soft Skills

  • Strong analytical, troubleshooting, and problem-solving abilities.
  • Ability to collaborate effectively with engineers, data scientists, and business stakeholders.
  • Excellent verbal and written communication skills, with the ability to explain defects and quality risks to technical and non-technical audiences.
  • Self-driven approach with strong attention to detail.
  • Ability to work effectively in ambiguous, fast-paced environments while managing multiple priorities.

Key Skills

Must-Have: QA, React, Python

Good-to-Have: AI/ML, GitHub Actions

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