QA Team Leader

ThetaRay is the leading provider of AI-based Big Data analytics.

We are helping financial organizations combat financial cybercrimes such as money laundering and fraud, and facilitating malicious crimes such as terrorist financing, narco-trafficking, and human trafficking, which negatively impact the global economy.

Join us as a QA Automation and performance TL to lead the Automation and performance team including HO tasks.

This role follows a hybrid model, involving being present at ThetaRay's Israeli site three times a week.

As a Team Lead, you will bridge the gap between high-level quality strategy and hands-on technical execution. You will be responsible for the growth of your team members, the stability of our AI-driven platforms, and the efficiency of our delivery pipelines.

Key Responsibilities

• Leadership & Mentorship: Lead and coach the Automation and Performance team. Set clear goals, conduct code reviews, and foster a culture of technical excellence.
• Strategic Planning: Define and implement E2E testing policies, standards, and procedures for solutions deployed to global Tier-1 financial institutions.
• Technical Architecture: Design and maintain scalable automation frameworks and performance testing suites using Python.
• Stakeholder Management: Partner with R&D, Product, and Delivery stakeholders to align quality initiatives with business roadmaps and system development life cycles.
• CI/CD Ownership: Build and optimize test pipelines within CI/CD environments to ensure fast, stable, and reliable deployments.
• Performance & Scale: Oversee performance testing strategies to ensure the platform handles massive Big Data workloads without degradation.
• Quality Governance: Act as the final authority on system/acceptance testing in NFT, providing risk assessments and "Go/No-Go" recommendations for releases.
  
  

• Experience: 10+ years in QA Automation and performance testing, with at least 7 years in Team Lead positions.
• Automation Mastery: 5+ years of hands-on experience developing automation infrastructures from scratch using Python.
• Backend Expertise: 5+ years of deep experience in Backend QA and API testing.
• Technical Stack: Strong proficiency in Linux shell and CI/CD utilities.
• Experience with Kubernetes, Microservices, and Cloud technologies (AWS/Azure/GCP).
• AI Focus: Experience with AI-based testing, specifically focusing on evaluation and observability (Significant Advantage).
• Education: B.Sc. in Computer Science or a related technical field.
• Languages: Proficiency in English.
• Communication: Proven ability to communicate complex technical risks to non-technical stakeholders.