Validation Engineer - Multi-Agent AI Systems (f/m/x)

We are building an inter-domain multi-agent system that spans ADAS, Infotainment and backend services for the intelligent vehicle of the future. A dedicated team designs and implements this system - your job is to prove it works. You will own the virtual validation of this multi-agent AI system in a cloud-based test environment, developing AI-assisted validation strategies that systematically explore the behavioural space of interacting agents and uncover failures that conventional testing would miss.

What awaits you?

• You build and operate cloud-based validation environments for a multi-agent system that operates across ADAS, Infotainment and backend-service domains - defining test architectures, scenario pipelines, behavioural oracles and regression suites.
• Also, you design AI-assisted exploration strategies to navigate the semantic search space of the system under test: agent-based probing of behavioural boundaries, adaptive test strategies, and optimization techniques to surface edge cases and failure modes.
• It is your responsibility to develop coverage models and metrics for non-deterministic multi-agent systems and use them to steer test generation and assess release readiness.
• You establish validation methodologies suited to stochastic AI behaviour: metamorphic testing, property-based testing, adversarial probing and acceptance criteria grounded in confidence intervals rather than binary pass/fail.
• You build observability and diagnostics tooling for validation runs - distributed tracing, trajectory replay, automated failure clustering and root-cause triage - so that discovered issues can be rapidly understood and communicated to the design team.
• Furthermore, you evaluate and select the LLMs/SLMs that power your validation agents and test-generation systems, balancing latency, cost and accuracy for large-scale test campaigns.
• You close the feedback loop between validation findings and system improvement by structuring discovered failures, coverage gaps and behavioural anomalies into actionable knowledge for the design and context-engineering teams.

What should you bring along?

• University degree in Computer Science, AI/ML, Systems Engineering, or a related field.
• 3 - 5 years of hands-on experience in validation, verification or quality engineering for complex AI, ML or software-intensive systems.
• Expert-level programming skills in at least one high-level language (C++, Java, Kotlin or Python).
• Proficiency in AI-assisted development using coding agents such as Claude Code, GitHub Copilot or OpenCode.
• Understanding of agentic AI architectures, agent patterns and multi-agent interaction.
• Ability to apply optimization, search or operational-research techniques (genetic/evolutionary algorithms, Bayesian optimisation, Monte Carlo methods) to testing or exploration problems.
• Experience with automotive software quality processes (e.g. ASPICE, ISO 26262) is a plus.

You enjoy working in an international team and are passionate about software quality? Apply now!

Find out more about Artificial Intelligence at the BMW Group here.

If you apply, the next stages of the recruiting process include an online test followed by technical interviews with the hiring manager (either virtual or in person).