Senior Quality Assurance Automation Engineer

We are a team to design, develop, maintain, and improve software for various ventures projects, i.e., projects that are adjacent to our core businesses and are bootstrapped fast with a lean team. You will be actively involved in the design of various components behind scalable applications, from frontend UI to backend infrastructure.

We are seeking a Senior QA Automation Engineer who combines deep expertise in mobile and API test automation with hands-on experience leveraging AI/LLM technologies to accelerate quality engineering. You will play a key role in building next-generation, AI-powered test automation systems that elevate the quality, efficiency, and intelligence of our testing pipeline for the Crypto.com App.

Responsibility: •   Design, develop and execute test plans and test cases with a strong emphasis on automation to shorten the test cycle and solve technical challenges through code. •   Develop, maintain and continuously improve test frameworks, tools and technologies — including AI-augmented test generation, intelligent test selection, and automated result analysis. •   Build and integrate AI-powered capabilities into our QA pipeline, such as LLM-based test case generation, smart deduplication, log/error analysis, and self-healing test scripts. •   Work with Development, Product Management and other QA engineers to design and implement effective test and validation strategies for new features. •   Estimate test efforts, analyze and communicate test results, and participate in day-to-day QA activities including defect triage and metrics reporting. •   Create, execute and troubleshoot automated test scenarios across mobile, REST and WebSocket APIs. •   Contribute to robust, scalable and high-quality test automation solutions for functional, regression and performance testing. •   Contribute to the building and maintenance of CI/CD environments and ongoing process improvement activities. •   Identify improvements in test and development processes; explore and prototype emerging AI tooling (LLM agents, embedding-based search, RAG pipelines) to address QA-specific needs. •   Mentor junior QA engineers and act as a technical reference within the team on automation best practices and AI-assisted testing. •   Maintain a high quality bar in a complex and constantly evolving workspace

Requirements: Core QA Automation (Must-have) •   5+ years of experience in mobile testing and automated test techniques, with a strong focus on quality throughout the entire software development cycle. •   Solid experience in REST and WebSocket API automation testing with Python / Java / JS. •   Hands-on experience with frameworks such as Pytest, Pytest-bdd, Appium, Selenium, Playwright, Cucumber, etc. •   Strong knowledge of object-oriented programming with solid coding and debugging skills. •   Strong design and development skills in Python / Java / JS. •   Good understanding of software design principles, patterns, algorithms, data structures and multi-threading concepts. •   Proven ability to translate functional requirements and use cases into working test plans and test cases. •   Working knowledge of Continuous Integration practices with Jenkins or GitHub Actions. •   Demonstrated skill in using coding standards and being an active participant in code reviews. •   Proficient English communication skills to adapt to a globalized work team.

AI / LLM Experience (Preferred — exposure or hands-on experience expected, deep specialization not required) •   Practical experience integrating heterogeneous LLM APIs (e.g., OpenAI, Anthropic) into engineering workflows or test tooling. •   Familiarity with prompt engineering and structured output parsing (e.g., Pydantic, Instructor) — including basic self-correction / retry mechanisms to ensure stable LLM outputs. •   Exposure to RAG pipelines and embedding-based retrieval, including using similarity (e.g., > 0.95 cosine similarity) for test case deduplication or recall. •   Working knowledge of at least one vector database (e.g., Milvus, Pinecone, Chroma, Weaviate). •   Hands-on experience with AI coding tools (e.g., Cursor, Windsurf, Claude Code, Copilot) and a habit of leveraging them to maximize delivery efficiency ("Vibe Coding" / AI-native mindset). •   Basic understanding of AI Agent concepts — ReAct, Memory, Tool Calling — and any experience designing or maintaining agent-based systems is a strong plus. •   Bonus: awareness of next-generation agent frameworks (e.g., LangGraph, multi-agent orchestration, Hermes Agent, OpenClaw) or interest in applying them to QA automation.

Nice to Have •   Experience working in an agile environment. •   Ability to work across Windows, Linux and macOS environments. •   Prior experience in fintech, crypto, or trading platforms. •   Passion for improving code quality through close collaboration with the development team.