Overview
Senior QA Automation Engineer Jobs in Abu Dhabi, UAE/Dubai at cander
Headquartered in Abu Dhabi, specializes in developing defense-grade artificial intelligence solutions to ensure high standards of reliability, reliability where large language models and predictive systems are tested rigorously. The company focuses on industries requiring mission-critical AI, integrating automated validation frameworks that meet strict evaluation criteria while supporting seamless ERP integrations and real-time data integrity. Their work emphasizes Agile development combined with formal Systems Engineering to deliver secure and traceable AI validation methods for high-stakes applications.
Job Summary
We are seeking a Senior QA Automation Engineer to lead the validation and verification strategies for our AI transformation initiative. In this critical role, you will define and enforce rigorous standards for non-deterministic AI systems, ensuring Large Language Models (LLMs) and predictive engines meet the stringent reliability requirements of the defense sector. Your expertise will bridge Agile development methodologies with formal Systems Engineering practices, creating automated testing frameworks that validate both software functionality and AI behaviors against established Ground Truth datasets.
Working within a structured Stage Gate delivery model, you will ensure AI agents successfully pass Test Readiness Reviews (TRR) and Functional Configuration Audits (FCA) before deployment. This role demands a deep understanding of AI evaluation techniques, including hallucination detection, consistency validation, and factual accuracy assessment, while also addressing integration challenges with enterprise systems like SAP S/4
HANA and Ariba. Your work will directly contribute to the trustworthiness of AI-driven decision-making in mission-critical applications, setting new benchmarks for how defense organizations validate intelligent systems. As the final line of defense, you will pioneer methodologies for testing Generative AI in safety-critical environments, ensuring AI agents are capable of negotiating contracts or designing system components with the highest levels of reliability and compliance.
Key Responsibilities
- Lead the validation and verification of AI systems by architecting automated testing frameworks to evaluate non-deterministic outputs, including hallucination detection, consistency checks, and factual accuracy against gold standard datasets for Large Language Models (LLMs) and predictive engines.
- Design and implement automated evaluation metrics such as RAGAS, faithfulness, and answer relevance to validate Retrieval-Augmented Generation (RAG) pipelines, ensuring accurate citation of internal technical documentation and regulatory texts.
- Develop prompt regression suites to monitor prompt drift and maintain the quality of AI-generated engineering documents, mitigating degradation risks from underlying model or system instruction changes.
- Construct robust integration tests to validate data consistency between AI agents and critical enterprise systems (e.g., SAP S/4
HANA, Ariba), ensuring no corruption of Bill of Materials (BOM) or financial data in supply chain applications.
- Create performance benchmarking tests to validate latency and throughput of forecasting models and risk scoring engines, aligning with real-time requirements for supply chain dashboards.
- Automate API validation for secure gateways, verifying Role-Based Access Control (RBAC) and Personally Identifiable Information (PII) redaction logic before data ingestion into AI models.
- Ensure alignment of automated test cases with System Requirements and User Needs, generating digital evidence for Verification and Validation (V&V) reports as per Systems Engineering Handbook standards.
- Prepare Test Readiness packages for Stage Gate reviews, providing quantitative evidence to demonstrate system stability and readiness for progression from Minimum Viable Product (MVP) to Production deployment.
- Manage the defect lifecycle between Requirements Quality Assistants and development teams, tracing defects in AI logic back to specific model versions or datasets for resolution.
- Bridge Agile development and formal Systems Engineering processes, ensuring AI agents meet rigorous Test Readiness Reviews (TRR) and Functional Configuration Audits (FCA) for defense-sector deployment.
Qualifications And Experience
- 5+ years of experience in QA Automation, with at least 2 years focused on testing complex data-driven applications, machine learning models, or AI agents.
- Experience in Defense, Aerospace, or highly regulated industries is a strong plus. Understanding of IV&V (Integration, Verification, and Validation) processes is highly desirable.
- Expert proficiency in Python for building custom test harnesses (Pytest) and standard automation libraries (Selenium/Playwright for UI, Requests for API).
- Expert proficiency in crafting Performance Test Plans and Implementations (e.g., Locust, Jmeter, K6).
- Experience utilizing frameworks for evaluating Large Language Models…
Title: Senior QA Automation Engineer
Company: cander
Location: Abu Dhabi, UAE/Dubai
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