We are looking for a Software Engineer to build AI-assisted workflows around semiconductor
engineering automation. This role is ideal for someone who enjoys LLMs, retrieval, tool-using agents, workflow automation, evaluation, and practical integrations with real engineering data and platform APIs.
WHAT YOU WILL DO:
- Build AI assistant workflows for engineering setup, troubleshooting, review, and knowledge retrieval.
- Connect tool-using agents to platform APIs, engineering data, documents, and automation workflows.
- Develop knowledge-ingestion pipelines for engineering practices, process rules, requirements, and
reusable workflow patterns.
- Create evaluation datasets and tests to verify assistant correctness, usefulness, and safety.
- Build workflow templates that help engineering teams standardize repeated tasks across programs.
- Develop integrations that let AI agents call real tools and return traceable, reviewable results.
REQUIRED SKILLS:
- Strong Python or TypeScript development skills.
- Hands-on exposure to LLMs, RAG, tool calling, agents, workflow automation, or API integration.
- Ability to build practical software, not just prompts or prototypes.
- Good debugging, testing, documentation, and integration habits.
- Strong communication skills and curiosity to learn engineering workflows.
- Comfortable using AI coding tools responsibly and validating outputs carefully.
Preferred Qualifications
Experience: 2-4 years
GOOD TO HAVE:
- LangChain, LlamaIndex, Semantic Kernel, MCP, vector databases, embeddings, or agent frameworks.
- LLM evaluation, prompt/version management, retrieval evaluation, or AI workflow testing.
- Backend or frontend integration experience.
- ML/data pipeline exposure.
- Experience building internal automation tools, engineering assistants, or knowledge systems.
- Exposure to semiconductor test, ATE, validation, CAD/CAE, or engineering automation domains.
