Conduct applied AI and machine learning research for semiconductor testing. Define ambiguous technical problems, develop measurable evaluation methods, build and fine-tune models, and create RAG, knowledge-graph, and agent systems. Translate unstructured tester documentation and protocols into production solutions, collaborate with engineering and domain experts, and deploy tools that improve workflows. The role also requires monitoring emerging AI technologies and proposing new research directions.

Leads and contributes hands-on to development of an AI engineering platform for semiconductor testing. Designs agent tooling, RAG systems, cloud and air-gapped inference infrastructure, Kubernetes platforms, reusable AI patterns, and agent-facing UIs. Sets technical direction, selects hardware and inference stacks, manages production systems, resolves cross-team architecture decisions, and guides a small engineering team. Requires strong distributed systems, software development, leadership, communication, and LLM/agent tooling expertise.

Drive regional growth for semiconductor ATE solutions across North America and Europe by identifying new revenue opportunities, enabling early design-ins, managing strategic accounts and partnerships, aligning product roadmaps with market needs, and coordinating cross-functional teams to convert opportunities into long-term customer engagements.