Senior QA Engineer - Vehicle Networks and Telematics

• Validation strategy and release qualification for CAN-based vehicle features, new vehicle onboarding and customer configurations.
• Requirement-to-test coverage for vehicle signals, diagnostics, power modes and end-to-end telematics workflows.
• Root-cause investigation of signal mismatches, intermittent CAN failures and vehicle-specific field issues.
• Reusable CAN simulation, trace replay, fault-injection and automated regression capabilities.
• Technical guidance through test-design reviews, automation reviews and structured defect triage.

• 3+ years of experience in QA or validation of embedded, automotive, telematics or IoT products, with substantial hands-on CAN work and a track record of owning test strategy, traceability and release-readiness decisions.
• Strong CAN 2.0A/B fundamentals, including 11-bit and 29-bit identifiers, arbitration, error handling and bus-off behavior.
• Hands-on expertise in SAE J1939, with working knowledge of OBD-II.
• Experience interpreting DBC files and validating raw frames, decoded signals, scaling, timing and invalid-data behavior.
• Hands-on experience with one or more CAN analysis and simulation platforms, such as Vector CANalyzer/CANoe, Intrepid Vehicle Spy, PEAK PCAN or Kvaser, and scripting in Python, CAPL or an equivalent language.
• Strong embedded-system debugging and root-cause analysis skills across hardware, firmware, network and backend boundaries, with the ability to explain technical risks and evidence clearly to cross-functional stakeholders.

• Understanding of CAN wake-up and sleep behavior, ignition concepts, power-state transitions and sleep-current measurement.
• Comfort working with vehicle harnesses, multimeters, programmable power supplies and bench equipment.
• Working knowledge of UDS (ISO 14229) and ISO-TP, including diagnostic sessions, reading and clearing DTCs, and reading data identifiers.
• Awareness of CAN FD and experience with HIL systems or ECU/network simulation.
• Exposure to J1708/J1587 on older heavy-duty vehicles.
• Python experience with libraries and frameworks such as python-can and pytest, including data-driven and parameterized testing.
• Experience with Linux-based environments, SocketCAN and can-utils (candump, cansend), shell tools, log analysis, Git and code-review workflows.
• Experience in fuel management, ELD/HOS (FMCSA), vehicle diagnostics, EV telemetry or other CAN-based fleet features.
• Experience using AI-assisted tools for test design, log triage or trace analysis.
• Experience with Jira, Confluence and CI-based automated testing for traceability, defect management and qualification reporting.

If there is a match between your experiences/skills and the Company's needs, we will contact you directly.

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• Validate SAE J1939 PGN/SPN decoding for vehicle speed, odometer, engine hours, fuel, DM1/DM2 faults and other supported signals.
• Validate OBD-II modes, PIDs, DTCs and VIN handling using SAE J1979 and ISO 15765-4.
• Verify scaling, offsets, units, ranges, rollover, timeouts, stale data, source-address handling and not-available values.
• Test J1939 transport protocol (BAM and RTS/CTS), request messages, address claim and bus-off recovery.
• Correlate device-decoded values with trusted CAN tools and OEM or dealer diagnostic systems.

• Validate wake-up on CAN traffic and ignition, sleep after bus silence, shutdown and recovery across supported configurations.
• Measure quiescent current and verify that the device causes no unwanted wake-ups, excessive bus traffic or vehicle battery drain.
• Validate ignition (KL15) and battery (KL30) scenarios, brownouts, power interruptions and repeated ignition cycles.

• Set up and execute bench, HIL and in-vehicle tests using CAN interfaces, programmable power supplies, ignition control and harnesses.
• Simulate ECUs, replay recorded traces, inject protocol and signal faults, and reproduce field scenarios in the lab.
• Validate integrations across commercial and passenger vehicles, makes, models and model years, including in fleet yards and at customer sites.

• Validate CAN-derived data from vehicle bus to cloud for fleet features such as fuel consumption, fuel-level trends, idle fuel, refueling and suspected fuel theft.
• Validate CAN-derived inputs supporting ELD/HOS workflows, including engine power state, vehicle motion, distance, engine hours and malfunction scenarios, against product requirements and the FMCSA ELD rule.
• Support validation of EV signals (state of charge, charging state, energy usage) and OTA/firmware regression for vehicle-specific releases.

• Translate product requirements, protocol specifications, DBC files and field use cases into risk-based, traceable test plans.
• Build maintainable Python, CAPL or equivalent automation for CAN simulation, trace replay, signal verification, negative testing and regression.
• Analyze CAN traces, device and application logs, power measurements and cloud telemetry to isolate failures across the vehicle, harness, firmware, configuration and cloud layers.
• Create clear defect reports with reproducible steps, trace evidence, expected versus actual behavior and impact.
• Work with development teams to close gaps in testability, diagnostics and observability.