QA Engineer Video & AI Analytics Platform (BLUE)

Opportunity to be a part of Worlds first Semantic Video Data Lake, an intersection of AI, video intelligence, and enterprise technology. Exposure to large-scale real-world deployments across multiple industries Collaborative and fast-paced product environment Competitive compensation and growth opportunities Ownership of quality in a high-impact, mission-driven platform Close collaboration with engineering, AI, and product teams Bachelor s degree in Computer Science, Engineering, or a related field 2 5 years of experience in QA/testing for SaaS, video platforms, or analytics systems Strong understanding of API testing using tools such as Postman and REST clients Familiarity with video streaming protocols including RTSP, HLS, and DASH Experience with automation frameworks such as Selenium, PyTest, Robot Framework, or Cypress Working knowledge of SQL/NoSQL databases for analytics validation Strong analytical and problem-solving skills with high attention to detail Experience validating AI/ML outputs and analytics systems is a plus Understanding of CI/CD workflows and automated testing pipelines Ability to work in a fast-paced, collaborative product environment Design and implement end-to-end QA strategies for video pipelines, APIs, and analytics dashboards Execute functional, regression, system, integration, and performance testing Validate CCTV workflows including video ingestion, compression, storage, and playback Monitor latency, frame drops, playback consistency, and video quality across formats such as H.264, H.265, and HLS Verify AI-generated outputs including dense captions, KPIs, and event detection accuracy Cross-check analytics results against ground truth data and business rules Develop and maintain automated test suites for APIs, dashboards, and analytics pipelines Integrate automated testing workflows into CI/CD pipelines for continuous quality assurance Design testing scenarios across industries including retail analytics, QSR monitoring, petro retail compliance, and manufacturing safety Collaborate closely with developers, AI engineers, and product managers to identify and resolve issues early Maintain detailed QA documentation including test plans, bug reports, release checklists, and validation reports Ensure platform scalability, reliability, and stability under real-world workloads We are looking for a detail-oriented QA Engineer to ensure the quality, reliability, and performance of BLUE s end-to-end video and AI analytics platform. You will be responsible for validating video ingestion, compression, AI pipelines, analytics accuracy, and reporting dashboards across multiple real-world industry deployments. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.