Senior Principal, Design Engineering

Summary

Celestica is accelerating the adoption of Artificial Intelligence and intelligent automation across its Hardware Engineering organization to improve engineering productivity, reduce manual effort, accelerate development cycles, and improve design quality and first-time-right execution.

We are seeking a senior AI Architect – Hardware Engineering to lead this transformation.

The AI Architect will define and drive the AI strategy for Hardware Engineering, identifying where AI can create meaningful engineering value and translating those opportunities into scalable solutions that can be deployed across the organization.

This is fundamentally a Hardware Engineering role. The successful candidate will bring deep experience in hardware product development and a strong understanding of engineering workflows, tools, processes, and challenges. The role is not a software or AI developer; rather, the successful candidate must understand AI technologies sufficiently to identify opportunities, define requirements, establish technical direction, and work effectively with internal AI/software resources and external technology partners to deliver solutions for Hardware Engineering.

This role will operate at the intersection of hardware engineering, AI technology, engineering tools, automation, and organizational transformation. The AI Architect will work closely with R&D engineering teams to identify high-value opportunities; partner with internal AI/software resources to develop solutions; evaluate external AI technologies and vendors; and establish an integrated roadmap for AI adoption across Hardware Engineering.

The successful candidate will also serve as the primary technical and strategic voice for Hardware Engineering AI initiatives, communicating vision, priorities, progress, business impact, risks, and resource requirements to engineering leadership and senior executives.

Knowledge/Skills/Competencies

Key Responsibilities

• Define and maintain the AI and intelligent automation strategy and roadmap for Hardware Engineering, grounded in a deep understanding of hardware development processes and engineering needs.

• Partner with electrical, mechanical, thermal, power, systems, simulation, reliability, compliance, and test/validation teams to identify and prioritize high-value AI opportunities.

• Drive AI opportunities from idea → prototype → pilot → production deployment → scaled adoption, working with Hardware Engineering teams, internal AI/software resources, and external partners.

• Translate hardware engineering problems, workflows, and requirements into clearly defined AI and automation solutions.

• Provide technical direction for AI-enabled engineering applications, copilots, agents, automation, and reusable capabilities without necessarily serving as the primary software developer.

• Evaluate external AI platforms and engineering tools based on their ability to solve real Hardware Engineering problems, including build-versus-buy-versus-partner recommendations.

• Partner with IT, Security, Legal, and Engineering stakeholders to ensure appropriate AI governance, data security, intellectual-property protection, and engineering validation.

• Establish measurable KPIs for AI initiatives, including engineering hours saved, cycle-time reduction, quality improvement, first-time-right performance, adoption, and return on investment.

• Serve as the central AI technology leader for Hardware Engineering, communicating vision, roadmap, progress, challenges, investment needs, and business impact to engineering leadership and senior executives.

• Drive adoption and reuse of successful AI capabilities across global Hardware Engineering teams.

Key Deliverables

• Hardware Engineering AI strategy and roadmap

• Prioritized AI use-case and investment portfolio

• AI-enabled Hardware Engineering workflow strategy

• External AI technology and vendor strategy

• AI solution deployment and governance framework

• AI adoption and KPI tracking

• Executive-level AI strategy, status, and business-impact reporting

Qualifications 

• Extensive Hardware Engineering experience, with a strong understanding of the hardware product-development lifecycle, engineering processes, design methodologies, and engineering tools.

• Experience across multiple hardware disciplines such as electrical design, system architecture, mechanical, thermal, power, simulation, reliability, compliance, or test/validation.

• Strong understanding of how AI, Generative AI, LLMs, AI agents, and automation can be applied to engineering workflows and technical problem solving.

• Demonstrated ability to translate complex Hardware Engineering challenges into technical requirements and scalable solutions.

• Strong systems-thinking, architecture, program leadership, and cross-functional collaboration skills.

• Ability to communicate effectively with Hardware Engineering teams, AI/software specialists, technology vendors, and senior executives.

#HPS-NA

Salary

Base Salary: $210,868 - $329,857

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

Required Experince :

A minimum of 12+ years of experince in Harwdware product development lifecycle. 

Preferred Experience

• Advanced AI Expertise: Deep experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs).
• Modern AI Tools & Agents: Strong familiarity with the latest LLMs and autonomous AI agents (e.g., Glean, Gemini Enterprise, Vertex AI, and Anthropic Claude).
• Hardware Engineering Lifecycle: Comprehensive understanding of the end-to-end hardware engineering process for hyperscalers, including schematics, Signal Integrity (SI), Power Integrity (PI), PCB layout, thermal, and mechanical design.
• EDA & CAD Software: Familiarity with industry-leading Electronic Design Automation (EDA) and engineering tools (e.g., Cadence Allegro, Siemens EDA, Cadence Sigrity, Keysight ADS, PTC Creo, and Simcenter Flotherm).

Typical Education

Education: 

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Systems Engineering, or a related hardware engineering discipline.

Preferred Education 

• Advanced AI Expertise: Deep experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs).

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.