QA Validation Specialist 100% Remote

Must Have:

• 3+ years of hands-on Penetration Testing experience focused on Automotive Embedded Systems, IoT Devices, or Specialized Hardware
• Bachelor's or Master's Degree in Computer Science, Cybersecurity, Computer Engineering, or related technical field
• Vulnerability Research and Reverse Engineering experience
• Embedded Security Testing and Fuzzing experience
• Experience testing automotive embedded targets including ECUs, gateways, vehicle computers, digital clusters, and connected vehicle platforms
• Automotive communication protocols: CAN / CAN-FD, Automotive Ethernet, SOME/IP, DoIP, LIN, FlexRay
• Wireless Security Testing experience: Bluetooth / BLE, Wi-Fi (802.11), LTE / 5G, NFC, UWB, RF / Keyless Entry Systems
• Firmware Extraction and Reverse Engineering
• Hardware-Level Security Testing
• Python and C/C++ programming experience
• Experience with Automotive Cybersecurity standards: ISO/SAE 21434, UNECE WP.29 R155, MITRE ATT&CK
• Strong understanding of Automotive E/E Architectures
• Experience developing comprehensive penetration testing reports and remediation recommendations

Strong Pluses:

• AI/ML-driven Security Testing
• AI-enhanced Fuzzing and Vulnerability Discovery
• Adversarial Machine Learning experience
• TensorFlow, PyTorch, or Scikit-learn experience
• RTOS experience: QNX, VxWorks, AUTOSAR OS
• Automotive Linux experience
• Microcontroller expertise: Infineon AURIX, Renesas RH850, ARM Cortex-R/M
• Hardware Security Modules (HSM/SHE)
• SDR Experience: HackRF, USRP
• Advanced Reverse Engineering using IDA Pro
• Fault Injection and Side-Channel Analysis
• Advanced Security Tools: Vector CANoe, CANalyzer, Vehicle Spy, Wireshark, Burp Suite, GNU Radio, Binwalk

Preferred Certifications:

• OSCP
• OSCE
• OSWE
• GXPN
• eCPTX
• Automotive Security Certifications
• IoT Security Certifications

Ideal Candidate Profile:

Highly technical Automotive Penetration Tester with proven experience identifying vulnerabilities in vehicle ECUs, gateways, high-performance vehicle computers, digital clusters, and connected vehicle platforms. The ideal candidate will possess strong expertise across offensive security, fuzzing, reverse engineering, automotive networks, hardware security, and vulnerability research. Experience supporting software-defined vehicles, connected vehicle ecosystems, and emerging AI-driven security methodologies is highly preferred.