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. 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.
Numbers & Facts
Location
Austin, TX
Description
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