Job Description: Mobile Application Test Engineer – AI-Enabled Testing

About Anblicks

Role Overview

Key Responsibilities

• Perform functional, regression, integration, end-to-end, and compatibility testing of Android and iOS applications.
• Test on real devices, simulators, and emulators across different OS versions and configurations.
• Analyze HTTP/HTTPS traffic using Charles Proxy to troubleshoot API requests, responses, and network-related issues.
• Debug application crashes and failures using Android Logcat and iOS device logs.
• Perform API testing using Postman and validate mobile-to-backend integrations.
• Design test scenarios, test cases, test data, and reusable automation utilities.
• Develop, maintain, and troubleshoot mobile automation frameworks.
• Perform root cause analysis and document defects with supporting logs, screenshots, and recordings.
• Leverage AI tools for test case generation, test automation, log analysis, and defect investigation.
• Validate AI-enabled features for response accuracy, relevance, consistency, and reliability.
• Collaborate with developers, product teams, and QA engineers to ensure release quality.

Required Technical Skills

• Strong understanding of SDLC, STLC, test design techniques, defect management, and risk-based testing.
• Hands-on experience with Android and iOS application testing on real devices and simulators/emulators.
• Strong working knowledge of Charles Proxy, HTTPS traffic inspection, and API troubleshooting.
• Experience analyzing Android Logcat and iOS application/device logs.
• Good understanding of REST APIs, HTTP/HTTPS, JSON, authentication, and client-server architecture.
• Programming knowledge in Java, Python, or JavaScript.
• Understanding of mobile application lifecycle, permissions, deep links, push notifications, and local storage.
• Experience with Postman, Jira, Git, and Agile methodologies.

Test Automation & Frameworks

• Hands-on experience with Appium or equivalent mobile automation frameworks.
• Understanding of Page Object Model/Screen Object Model and reusable framework components.
• Experience with test runners, test data management, reporting, synchronization, and flaky test troubleshooting.
• Familiarity with TestNG/JUnit, Maven/Gradle, and CI/CD integration using Jenkins or similar tools.
• Ability to debug, enhance, and maintain scalable automation frameworks.

AI, LLM, RAG & AI Agents

• Understanding of Generative AI, LLMs, prompt engineering, and AI-assisted testing.
• Exposure to AI-driven test case generation, test script assistance, and automated defect analysis.
• Knowledge of LLM evaluation, including response accuracy, relevance, consistency, and hallucination detection.
• Understanding of RAG pipelines and testing retrieval accuracy, source grounding, and response quality.
• Familiarity with AI agents, tool calling, API integrations, error handling, and task completion validation.
• Awareness of responsible AI practices, data privacy, and prompt injection risks.

Good to Have

• Experience with BrowserStack, Sauce Labs, or cloud-based mobile testing platforms.
• Exposure to LangChain, LlamaIndex, LLM APIs, or vector databases.
• Familiarity with AI evaluation tools such as RAGAS or DeepEval.
• Knowledge of SQL, mobile performance testing, application security, and CI/CD pipelines.