AI Application Engineer

Location

United States

Posted

52 days ago

Salary

0

Seniority

Mid Level

Job Description

AI Application Engineer

Advantest

Role Description This role sits at the intersection of semiconductor test engineering and AI, driving the transformation of traditional test workflows into AI-powered systems. As a member of the US AI R&D team, you will work closely with 93K R&D engineers, AI engineers, and data scientists to define, develop, and deploy next-generation AI capabilities for the V93000 platform. As an AI Application Engineer, you will act as the bridge between semiconductor test engineering workflows and AI systems, enabling step-change improvements in productivity such as: - Test program generation - Debug and root cause analysis - Knowledge-driven engineering workflows You will lead customer engagements for AI solutions, serving as the primary interface for: - Use case discovery - Product definition - Feedback and iterative improvement - Rollout and adoption of new capabilities You will collaborate with global R&D teams to influence product direction and strategy for AI-enabled test solutions. You will design and execute pre-sales and proof-of-concept activities, including: - Customer demos - Benchmark studies - Pilot deployments You will stay current with advances in AI/ML (e.g., LLMs, RAG, agent workflows) and drive internal and external enablement through workshops and training. Technical Environment: - Linux-based systems (e.g., Red Hat Enterprise Linux) - V93000 / SmarTest development ecosystem - Modern AI-assisted development workflows, including: - AI-enabled IDEs such as VS-Code, Cursor, GitHub Copilot, and Visual Studio Code - Markdown-driven prompt and agent design - Python-based automation and AI tooling - API-driven systems, version control (Git), and integration with AI platforms and services Qualifications - Degree in Electrical/Electronics Engineering or equivalent - Strong experience as an Application Engineer on the V93000 platform - Solid understanding of AI concepts applied to engineering workflows, such as: - LLMs - Retrieval-augmented generation (RAG) - Automation and code generation - Strong software skills (Java and Python), including: - Test program development - Scripting or tool development - Proven ability to translate customer problems into scalable technical solutions - Excellent customer-facing and pre-sales experience - Strong debugging, analytical, and problem-solving skills - Ability to lead cross-functional projects and drive outcomes - High ownership mindset: proactive, self-directed, and execution-focused - Comfortable working in global, cross-functional environments - Curiosity and drive to stay at the forefront of AI innovation - Willingness to travel internationally (20–30%) - Candidates throughout the United States are welcome to apply; remote work options may be available.

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