This engineer integrates an LLM (Claude API) into two parts of the pipeline: an offline classification pass that labels component intent during reference board ingestion, and an online fallback reasoning pass that generates placement recommendations when no reference pattern is found. Output from the LLM feeds directly into downstream automated logic, so reliability, structured output, and failure handling are critical.
Key Responsibilities
Required Skills:
• Claude API or equivalent (Anthropic SDK / OpenAI SDK), with experience generating structured, schema-constrained output (JSON) from LLM calls
• Prompt engineering for classification tasks: given component type, value, net names, and placement context, classify intent and signal class reliably
• Validation and failure handling: detecting malformed output, hallucinations, and low-confidence responses; defining fallback behavior
• Experience with confidence scoring and explainability — the system shows LLM reasoning to the designer, so output must be human-readable and trustworthy
Other Requirements
1. Optional But Valuable Certifications: Certified Test Engineer (Cte), Ipc Certified Interconnect Designer (Cid), Or Relevant Industry-Standard Certifications.
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