QA Team Lead – Cyber & AI

Description:

Every nation has data. Few can protect it. Fewer still can act on it.

Dream is the sovereign AI and national cyber-defense company for governments.

We help nations secure their most critical systems, connect fragmented information at a national scale, and turn their most sensitive data into decisions, all fully sovereign.

This is more than a job. It's a Dream job, where you'll work at a global scale alongside some of the best AI researchers, cyber operators, and government experts in the world.

We defend nations against the most advanced threats in the world with a national security suite that offers AI-native resilience against APTs with visibility, insights and mediation across Posture, CTI, and Detection & Response, all fully sovereign.

We are looking for a technically strong, hands-on QA Team Lead to lead a team of approximately five QA engineers and drive the quality of our cybersecurity product. 

In this role, you will combine people management with technical leadership, guiding the team’s manual, exploratory, and API testing efforts. You will own QA delivery from initial planning through production release, working closely with development, product, and automation teams to align priorities, resolve dependencies, and deliver high-quality releases. 

You will also help the team use AI tools effectively in everyday work, improving test coverage, investigation, and efficiency while applying sound technical judgment. 

• Lead, mentor, and develop a team of approximately five QA engineers through regular feedback, coaching, and professional development. 
• Own QA planning and delivery across multiple features, balancing team capacity, release timelines, and product risks. 
• Drive testing activities end to end, clarify requirements, define scope, coordinate dependencies, track execution, and ensure completion. 
• Partner with development, product, and automation leads to align expectations, surface risks early, and resolve blockers. 
• Participate in feature kickoff and design discussions, identifying testing needs, environment and dataset requirements, and potential coverage gaps. 
• Define and review test strategies and test plans, ensuring meaningful coverage of functional, exploratory, regression, integration, end-to-end, and API scenarios. 
• Remain hands-on with complex testing and technical investigations, using APIs, logs, and system behavior to isolate failures and support root cause analysis. 
• Lead defect triage and communicate release readiness, outstanding risks, and QA recommendations clearly to stakeholders. 
• Collaborate with automation engineers to prioritize automation coverage and maintain an effective balance between manual and automated testing. 
• Establish practical AI workflows for test planning, edge-case discovery, log analysis, and defect investigation; coach the team to validate outputs and assess their value. 
• Improve QA processes, testing standards, and documentation, using coverage gaps, escaped defects, and testing bottlenecks to guide priorities. 
• Support production issue investigations and ensure lessons learned are reflected in future testing.