The AI Application Engineer drives AI transformation in semiconductor test workflows, leading customer engagements and collaborating globally to deploy innovative AI solutions.
Job Summary & Responsibilities
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
- 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.
Similar Jobs
Retail
Design, build, and iterate AI agents, copilots, and assistant experiences using Microsoft Copilot Studio, Azure AI, and Power Platform. Configure knowledge sources, partner with stakeholders to prototype solutions, evaluate agent performance, refine prompts and grounding, and document and package reusable templates toward production readiness.
Top Skills:
APIsAzure AiAzure Ai StudioAzure OpenaiDataverseEnterprise SearchMicrosoft Copilot StudioMicrosoft GraphMicrosoft TeamsPower AppsPower AutomatePower PlatformRetrieval-Augmented GenerationServicenowSharepointSQL
Consulting
As a Senior Application Developer, you will define, develop, and deploy software solutions, collaborate with clients, and implement AI features within applications.
Top Skills:
.NetAWSAzureC#DevOpsGCPIotJavaJavaScriptMachine LearningPythonRestful ApisSQL
Artificial Intelligence • Cloud • Internet of Things • Software • Cybersecurity • Industrial
Lead end-to-end data architecture and analytics for Parts Sales to End Users (STU): design Snowflake data models, build scalable data pipelines, develop Power BI dashboards, support forecasting and ML models, validate data quality, drive automation and system modernization, and communicate insights to senior stakeholders to improve reporting, forecasting, and business decisions.
Top Skills:
AlteryxAws Ec2Aws GlueAws LambdaAws S3Azure DevopsDeep LearningMachine LearningPower BIPythonRSnowflakeSQL
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center



