We are hiring an experienced, forward-thinking Automation Team Lead to lead the evolution of our quality engineering practices into an AI-driven testing ecosystem.
In this role, you will lead a global team of automation engineers while shaping the next generation of intelligent testing-leveraging AI/ML, generative AI, and data-driven approaches to dramatically improve quality, coverage, and delivery speed.
You will combine hands-on leadership with strategic thinking, driving both execution and innovation in how we validate complex security systems.
Responsibilities:
Lead, mentor, and grow a team of automation engineers, fostering engineering excellence and innovation.
Own the teams deliverables, quality outcomes, and technical direction.
Design and implement scalable automation frameworks using Java, Selenium, and modern tooling.
Drive adoption of AI-powered testing approaches, including:
Using LLMs to generate, refine, and prioritize test scenarios based on requirements, code, and production data.
Intelligent test maintenance and self-healing mechanisms.
Risk-based and predictive testing using data insights.
Define and execute an Agentic vision for QA, balancing practical impact with long-term innovation.
Integrate automation into CI/CD pipelines to enable fast, reliable releases.
Collaborate with R&D, DevOps, and Product to ensure high-quality delivery.
Review user stories and requirements with a quality-first mindset.
Support and guide manual testing where needed, evolving it toward automation and AI augmentation.
Establish and maintain QA standards, methodologies, and best practices.
Promote a shift-left quality strategy, including observability and production validation.
Work in an Agile (Scrum) environment.
Requirements: Requirements:
2-3 years of experience leading QA Automation teams (preferably global teams).
5+ years of hands-on experience in software development (Java or C#).
Hands-on experience in applying AI to improve testing efficiency, coverage, or quality (e.g., test generation, failure analysis, or automation acceleration).
Familiarity with AI-assisted coding tools (e.g., Copilot, Cursor).
Understanding of concepts like:
Test generation using AI.
Good understanding of Prompt Engineering principals.
Proven ability to effectively use AI chatbot tools (e.g., ChatGPT) for tasks such as test scenario creation, troubleshooting, and workflow optimization.
Experience working with AI-powered coding assistants (e.g., GitHub Copilot, Cursor) within development environments.
Proven ability to effectively use/develop AI Agents.
Proven ability to effectively use/develop/configure MCPs.
Proven ability to effectively use/develop skills.
Self-healing tests.
Flaky test detection and prediction.
Ability to evaluate and integrate emerging AI tools into QA workflows.
Proven experience in building and scaling automation frameworks.
Strong experience with Selenium and API testing.
Experience in manual QA and test design.
Experience in networking - mandatory.
Strong problem-solving skills and ability to operate in a fast-paced environment.
Excellent communication skills in English.
Mindset of continuous innovation and experimentation.
Advantages:
Experience in QA of network security products.
Experience working with Firewalls.
Experience with AWS/cloud environments.
Experience testing complex systems (UI, API, DB).
Experience in Linux/Unix environments.
Experience building internal tools or platforms for QA productivity.
Background in data analysis or metrics-driven quality engineering.
Experience with developing MCPs.
Experience with transforming non-agentic system/SDLC into agentic system/ SDLC.
Experience with RAG pipelines and semantic search (vector databases).
This position is open to all candidates.