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Working Timing (6:30 pm - 2:30 am) Work mode: Remote Experience Required: 3-6 Years Salary Package: 12- 24 LPA Job Summary We are looking for a Senior Automation Test Engineer to lead the adoption of AI-powered software testing methodologies, where intelligent agents, AI-assisted test generation, self-healing automation, risk-based test optimization, and natural-language-driven testing become the primary approach to quality engineering. . The role combines hands-on automation engineering with the design and implementation of modern AI-assisted testing frameworks, integrating conventional automation where appropriate while driving the transition toward AI-first quality engineering. Beyond building automation, the position involves understanding why a testing practice may not be landing with a particular team and adjusting the approach - which requires reading organizational context, not just technical systems. Key Responsibilities Define the AI Testing Practice Design AI-first testing strategies, implementation frameworks, governance standards, and best practices that enable consistent adoption across engineering teams. Evaluate emerging AI-powered testing platforms, autonomous testing agents, and automation frameworks, recommending the most suitable approach for each project. Define how AI is applied throughout the testing lifecycleincluding requirements analysis, test generation, test maintenance, execution, defect triage, root-cause analysis, and reportingwhile establishing appropriate human review and governance checkpoints. Establish metrics and success criteria to measure the effectiveness, quality, and business value of AI-assisted testing. Build & Implement Automation Design, build, and maintain automation frameworks and scripts for web, mobile, API, and integration testing. Integrate AI-powered testing capabilities into CI/CD pipelines, enabling automated quality gates, intelligent release validation, and continuous feedback. Roll out testing practices directly with engineering teams and, where required, at client locations Drive AI Adoption & Engineering Enablement Assess the testing maturity of engineering teams and create practical adoption roadmaps for transitioning from conventional automation to AI-assisted testing. Mentor engineers and testers on AI-enabled testing techniques, responsible AI usage, prompt engineering, and modern quality engineering practices. Establish reusable templates, playbooks, and implementation patterns that allow AI-powered testing methodologies to scale across multiple projects and teams. Improve Through Feedback Identify why a testing approach or automation practice isn't being adopted by a team, and adjust it based on the root cause rather than assumption. Capture what works and what doesn't from each rollout and feed it back into shared standards and frameworks. Coordinate with development and deployment teams to ensure testing connects smoothly with what comes before and after it in the delivery pipeline. Required Skills Automation & Quality Engineering 36 years of hands-on experience in automation testing and quality engineering, across web, mobile, API, and integration testing. Solid hands-on experience with automation frameworks such as Playwright, Selenium, Cypress, Appium, or similar. Experience designing, building, and maintaining scalable automation frameworks, not just individual test scripts. Strong understanding of testing methodologies, test design techniques, and quality assurance best practices. Experience integrating automated testing into CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps. Strong understanding of release validation, deployment testing, smoke testing, and quality gates. Strong understanding of Git and cooperative development workflows. AI Tools & Usage - Hands-on, daily experience using AI-powered testing tools and assistants for test generation, automation development, defect analysis, and reporting. - Working knowledge of more than one AI tool or model, and the judgment to choose the right one for a given task. - Experience evaluating current or emerging AI testing tools and recommending which to adopt. - Ability to write transparent, effective prompts and instructions to get accurate, usable output from AI tools, and to catch and correct AI mistakes. - A genuine, active interest in keeping up with new AI tools, models, and techniques as they evolve. - Communication - Strong written and spoken communication skills in English - Strong interpretation skills: the ability to read organizational and stakeholder context, understand why a process or practice isn't working, and not treat every implementation issue as a technical one. - Ability to clearly explain testing strategy, findings, and AI-adoption recommendations to both technical and non-technical stakeholders, including in client-facing settings.Preferred Skills - Familiarity
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.