AI Application Engineer

Job 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

You will work in a hybrid environment combining:

• 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

Requirements: Requirements

• 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.