Lead the hands-on design and coding of RAG (Retrieval-Augmented Generation) architectures and agentic workflows.
Build systems that allow hardware engineers to "query" complex design rules and legacy data with high accuracy.
Write custom Python scripts and parsers to extract structured intelligence from diverse sources, including PDF datasheets and EDA output files.
Execute fine-tuning runs for foundation models (e.g., Gemini/Vertex AI) using proprietary historical data.
Develop capabilities for AI to interpret visual engineering data to automate technical documentation and manuals.
Implement "Shift-Left" algorithms that utilize historical yield and manufacturing data to predict potential defects.
Build and optimize the vectorization pipeline (using Pinecone, Milvus, or similar).
Act as a subject matter expert (SME) for AI/ML within the engineering organization and manage relationships with key AI research partners.

10 to 15+ years of related experience
Bachelor of Engineering (EE/ Computer Science/ Computer Engineering) or strong portfolio of technical leadership
Strong evidence of building and deploying AI-powered applications
Ability to write clean, scalable, and efficient Python code
Ability to extract signals from unstructured data, including complex technical PDFs and log files
Demonstrated ability to turn user requirements into functional AI features
Interest in PCBs, schematics, and manufacturing processes (good-to-have)
Experience with Google Vertex AI or similar enterprise platforms (good-to-have)
Background in Complex Systems, experience in datacenter solutions for Hyperscalers (good-to-have)
MS or PhD in a relevant field (EE, Computer engineering, Computer Science) (good-to-have)

Senior Principal, Design Engineer

Key skills