Test Automation Engineer (In-Vehicle Infotainment)

Project description

The software testing paradigm is shifting from manual execution to intelligent automation. At Luxoft, we are building a next‑generation AI‑powered testing platform that does not just run predefined test scripts, but autonomously generates test cases, adapts to requirement changes, and continuously improves coverage based on real‑world feedback. As part of this initiative, we are developing a system that ingests product requirements and design specifications, intelligently derives test design perspectives, and generates high‑quality test cases using AI agents. The platform covers the full testing lifecycle—from test case generation and execution on test benches to result analysis, defect triage, and reporting. This is a unique opportunity to shape how automotive software testing is done at scale, moving from manual effort to an AI‑assisted workflow that reduces time, increases coverage, and ensures traceability across vehicle programs.

Responsibilities

• Execute & Validate: Execute test cases on test benches according to the defined test plans, ensuring accurate setup, data capture, and repeatability. Setup & Configure: Set up and configure software stacks (middleware, drivers, application layers) according to feature specifications and test environment requirements. Triage & Analyze: Perform detailed triage and root‑cause analysis on test failures, log defects with clear reproduction steps, and track issues throughout the validation cycle. Collaborate & Verify: Work closely with firmware and software developers to clarify issues, provide supporting data, and verify fixes in subsequent test runs. Document & Report: Prepare and maintain detailed test reports with clear traceability to requirements, ensuring all results meet customer reporting standards. Improve & Automate: Contribute to test automation initiatives, develop scripts to improve efficiency, and continuously enhance test execution processes. Support & Regress: Support SQA activities including regression testing, build verification, and integration validation across bench and vehicle levels.

SKILLS

Must have

• Strong Linux working knowledge Experience in trouble shooting on both S/W and Hardware levels Proficiency in Python Knowledge on Classic Autosar/ Adaptive Autosar topologies preferred with working knowledge on XCP/CCP protocols Knowledge of AI agents and prompt Working knowledge on Vehicle networks and diagnostics Software update and OTA experience preferred. Outstanding ability to work in an extremely fast paced environment with an eye for details and analyzing bugs to report 20- 30% of travel may be required.

Nice to have

Excellent communication and collaboration skills - ability to work across multidisciplinary teams (systems, hardware, firmware, SQA). Strong problem‑solving mindset and ability to work under tight schedules. Proactive in proposing improvements to test methodologies and toolchains. Fluent in English (spoken and written);