Principal, Design Engineering

General Overview

Job Title: Principal, Design Engineering
Functional Area: Engineering (ENG)
Career Stream: Engineering (ENG)
Role: Principal (PRI)
Job Code: PRI-ENG-DSGN
Job Band: 12
Direct/Indirect Indicator: Indirect

Summary

We are looking for a high-impact Principal AI Engineer to architect, design, and code the next generation of our engineering intelligence platform. In this role, you will bridge the gap between advanced Generative AI and complex hardware engineering. Reporting to the Office of the VP of Engineering, you will lead the technical development of our "Celestica-tuned Enterprise LLM," transforming massive repositories of global engineering data into active, predictive intelligence.

This is a hands-on development role. You will be the lead developer responsible for building the data pipelines, RAG architectures, and multimodal models that allow our engineers to "talk" to their design tools and legacy data. You will work closely with hardware Subject Matter Experts (SMEs) to transform schematics, logs, and diagrams into a high-performance tool that our designers use daily to reduce board spins and accelerate time-to-market.

Detailed Description

Job Title: Principal AI Engineer – Hardware Design Automation (Hands-on Lead)

Location: San Jose, CA

Position Summary

We are looking for a high-impact Principal AI Engineer to architect, design, and code the next generation of our engineering intelligence platform. In this role, you will bridge the gap between advanced Generative AI and complex hardware engineering. Reporting to the Office of the VP of Engineering, you will lead the technical development of our "Celestica-tuned Enterprise LLM," transforming massive repositories of global engineering data into active, predictive intelligence.

This is a hands-on development role. You will be the lead developer responsible for building the data pipelines, RAG architectures, and multimodal models that allow our engineers to "talk" to their design tools and legacy data. You will work closely with hardware Subject Matter Experts (SMEs) to transform schematics, logs, and diagrams into a high-performance tool that our designers use daily to reduce board spins and accelerate time-to-market.

Knowledge/Skills/Competencies

• Advanced AI & Machine Learning: Deep theoretical and practical understanding of Large Language Models (LLMs), Natural Language Processing (NLP), and Multimodal AI architectures.

• Retrieval-Augmented Generation (RAG): Expertise in designing advanced RAG systems, vector embeddings, and semantic search principles to eliminate AI hallucinations.

• Data Architecture: Strong knowledge of data normalization, structuring unstructured data, and database management (specifically vector databases like Pinecone or Milvus).

• Hardware Engineering Lifecycle (Preferred): Familiarity with hardware design processes, Electronic Design Automation (EDA) tool outputs, Bill of Materials (BOMs), schematics, and manufacturing yield metrics.

• Google AI Ecosystem (Preferred): Specific knowledge of Google's Gemini model family, Vertex AI Agent Builder, and Model Garden.

Physical Demands

Salary

Salary Range: $150k- $215k Annually

The salary range described in this posting is an estimate by the Company, and may change based on several factors, including by not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.

Compensation includes the Base Salary and the target Short-Term Incentive (STI)/ bonus.  A comprehensive benefits package is offered in addition to this.

The stated range includes Base Salary and target Short-Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range.

The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.

Typical Experience

• .Experience: 5+ years of total software engineering experience, with at least 2+ years of hands-on coding in LLM application development, NLP, or Machine Learning.
• Hardware Lifecycle Coding: Proven experience building tools specifically for the hardware design cycle.
• Technical Stack: Expert proficiency in Python, PyTorch/TensorFlow, and vector databases. Mastery of LLM frameworks.

Typical Education

Education: A Master’s degree (MS) in Computer Science, Data Science, Electrical Engineering, or a related technical field is required. A Ph.D. in AI, Machine Learning, or Data Science is highly preferred

Notes

This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.