Advantest is seeking a Senior Principal AI Test Automation Engineer to
design and deliver reliable automation for complex engineering and production
test environments.
This role combines advanced test engineering, software automation, CI/CD, and
AI-enabled workflows. You will build repeatable systems that validate, execute,
monitor, and diagnose technical workloads across laboratory and production
environments.
We are looking for a hands-on technical leader who understands both physical
test systems and modern software architecture.
Key Responsibilities
- Architect production-grade test automation and CI/CD pipelines.
- Automate build, validation, execution, artifact collection, analysis, and
release gating.
- Integrate AI-generated recommendations into controlled engineering
workflows.
- Define validation and approval gates before automated actions interact
with hardware.
- Build structured interfaces between AI systems, test software, instruments,
and data services.
- Develop failure classification, diagnostics, recovery, and escalation
processes.
- Create reproducible execution environments using containers and version
controlled configurations.
- Establish observability, regression testing, and evidence-based release
criteria.
- Mentor engineers and set technical standards for automation and
production readiness.
Required Qualifications
- Extensive experience developing automation for advanced test or
measurement systems.
- Strong digital and mixed-signal test-engineering experience.
- Proven ownership of CI/CD systems using Jenkins, GitLab CI, or similar
platforms.
- Strong understanding of test programs, specifications, patterns,
instruments, limits, characterization, and result data.
- Strong Python and software-architecture skills.
- Experience with typed APIs, structured schemas, automated testing, and
version control.
- Experience integrating software with hardware, instruments, or laboratory
environments.
- Ability to lead architecture decisions and solve ambiguous technical
problems at Senior Principal level.
- Strong communication and cross-functional collaboration skills.
Preferred Qualifications
- Experience integrating AI or machine-learning capabilities into engineering
systems.
- Familiarity with AI agents, structured actions, evaluation gates, or human
approval workflows.
- Experience with containerized applications, automated characterization,
and multi-version execution environments.
- Experience working in secure or intellectual-property-sensitive
environments.
- Familiarity with Java or other hardware-control and test-development
languages.
What Success Looks Like
During the first year, you will:
- Deliver a trusted and repeatable automated test-execution pipeline.
- Establish clear validation, observability, and failure-diagnosis standards.
- Integrate AI-assisted recommendations into controlled and measurable
workflows.
- Reduce manual processes and convert expert knowledge into reusable
automation.
- Build a foundation that can support future projects through configuration
rather than one-off development.
Ideal Candidate
You are a deeply technical test engineer who also thinks like a software
architect. You understand that automation must produce reliable evidence—not
simply a successful pipeline result.
You can connect AI capabilities to real engineering environments while
maintaining validation, traceability, safety controls, and expert oversight.
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