Establish a robust, scalable, and cost-effective test automation strategy that aligns with short-term release goals and long-term product vision for a low-latency trading environment.
Champion the research, proof-of-concept, and full implementation of AI-powered testing tools, specifically focusing on utilizing the Model Context Protocol (MCP) with Playwright in Python to build adaptive, self-aware test suites that understand system changes and minimize maintenance effort.
Lead, mentor, and coach Senior, Mid, and Junior Automation Engineers, fostering a culture of engineering excellence, high coding standards, and deep system-level understanding.
Represent QA in architecture reviews and design discussions, ensuring testability is baked into the system design from inception, especially for distributed microservices.
Lead the design and development of advanced, polyglot test automation frameworks (API, UI, Database, Mobile) ensuring they are scalable, highly maintainable, and adhere to best-in-class design patterns.
Define and manage the strategy for high-frequency performance and load testing, focusing on latency and throughput benchmarks critical for a Forex trading platform.
Collaborate closely with DevOps to optimize the continuous testing pipeline (CT), ensuring full test suite execution is a seamless, fast, and mandatory gate in the CI/CD flow (e.g., Jenkins, GitLab CI).
Design test automation solutions that effectively gather and utilize system context and behavior data to enhance testing coverage and pinpoint complex issues, feeding into the Model Context Protocol (MCP).
Requirements
7+ years of hands-on experience in QA automation, with at least 2+ years in a leadership or senior mentorship role within a FinTech, Forex, or high-transactional platform environment.
Expert-level coding skills in at least one modern language (e.g., Python, Java, JavaScript) and a deep understanding of object-oriented design and automation patterns.
Strong, demonstrable background in performance, load, and stress testing using tools like k6, Locust, with specific experience analyzing low-latency network metrics.
Expertise in integrating automation into modern CI/CD pipelines (Jenkins, GitLab CI) and working with containerization (Docker, Kubernetes) for scalable test environment management.
Proven understanding or hands-on experience working with AI/ML testing concepts, specifically around Model Context Protocol (MCP), adaptive testing, or self-healing techniques driven by system context.
Experience with integrating and leveraging specialized AI/ML tools to enhance testing intelligence and coverage.
Solid understanding of financial market concepts, trading platform functionalities, and the necessity of high data integrity and precision.
Benefits
Hybrid Work Model (2 days working from home).
22 days of Annual Leave (reaching up to 30 days per year based on years' service)
Comprehensive Health & Life Insurance (from day one!)
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