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Responsibilities
Roles & Responsibilities
Testing :
Understand business requirements and design/develop robust manual test cases focusing in end user deployments.
Analyze business requirements and develop robust automation suites for the defined scope. Execute and identify 30 % issues via automation & CI/CD daily runs.
Ensure 100% end-to-end test coverage through test automation, ensuring product development aligns with business needs.
Expert in Performance Engineering and have experience in using any one of these performance testing tools- LoadRunner/Jmeter/Gatling/WebLOAD/ NeoLoad
Test Strategy & Lab Architecture: Design, implement, and own comprehensive test plans, methodologies, and specialized lab setups (using charts like Imatest, ISO standards, and controlled lighting environments) for advanced CCTV evaluations
Technical Mentorship & Collaboration: Provide technical guidance to junior QA engineers and present detailed test plan, regression, reliability, and risk-assessment reports to cross-functional R&D stakeholders
Advanced Image quality & Optics Benchmarking: Lead objective and subjective evaluation of critical image quality metrics (SNR, dynamic range, spatial resolution/MTF, color rendering, and low-light sensor performance)
Test Automation Development: Architect and maintain automated test scripts (primarily using Python, MATLAB, or C++) to parse test video streams, simulate environmental shifts, and automate data collection
Test Environment Planning
Plan and estimate test environment requirements based on release Requirement, roadmap, project demands and capacity Design environment strategy
Creation of new environments with the help of Coordinate with Infra, Network, DBA, DevOps and Vendor teams
Ensure all test environments are up, running and in working condition 24x7
Maintain SOPs, environment architecture diagrams, access list, inventory tracker
Qualifications
Mandate Skills
- Experience: 8 to 10 + years in engineering R&D environments specializing in camera validation, Image Signal Processing (ISP) tuning, or embedded multimedia systems.
- Core Knowledge: Strong foundation in camera systems architecture, optical principles (lenses, FoV, apertures), and CMOS sensor behaviors.
- Tools Expertise: Proficiency with Imatest (or similar IQ analysis suites), video stream analyzers, and oscilloscope/logic analyzers.
- Programming: Hands-on scripting experience in Python, Linux shell, or C/C++ to build robust automation suite for camera feature and Integration testing with headend system.
- Network & Embedded Protocols: Experience with RTSP/RTP protocols, H.264/H.265 compression algorithms, and hardware serial interfaces- Fair understanding of compliance with global and local deployment regulations (such as STQC, ONVIF, or NDAA) related to camers.
- AI Analytics Validation: Design and execute test matrices to validate the accuracy, precision, and latency of edge-AI algorithms (e.g., Object Detection, Facial Recognition, Automatic Number Plate Recognition (ANPR), and Intrusion Alerts).
Soft Skills
Proactive, ownership and Delivery mindset
Strong analytical , RCA and Problem-solving skills
Good communication and stakeholder management
Able to work under pressure and support quality on time release.