AI Engineer

Mission

Build and evolve an internal AI Operating System for the Design Department, enabling AI-assisted specification analysis, code generation, knowledge retrieval, and workflow automation while seamlessly integrating with existing EDA tools, engineering platforms, and design processes.

Role Overview

The AI Engineer will lead the strategy, architecture, deployment, and operationalization of AI technologies across the Design organization. This role is responsible for implementing and managing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, AI agents, and workflow automation frameworks that enhance engineering productivity and accelerate innovation.

The successful candidate will work closely with Design, Product Design, IT, and business stakeholders to transform engineering knowledge into scalable AI-assisted workflows, while ensuring robust governance, compliance, and alignment with organizational objectives.

Key Responsibilities

• AI Strategy and Roadmap

  • Develop, maintain, and execute the Design Department's AI roadmap, identifying opportunities to leverage AI technologies for engineering efficiency, innovation, and business impact.

  • Define the vision and architecture for an internal AI Operating System that supports specification analysis, code generation, knowledge management, and design workflow automation.

  • Evaluate emerging AI technologies, platforms, frameworks, and industry best practices for potential adoption and integration.

• AI Platform Architecture and Development

  • Design, deploy, and maintain AI solutions including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, AI agents, and workflow automation frameworks.

  • Build scalable AI platforms and infrastructure that integrate with existing EDA tools, engineering databases, documentation repositories, and design workflows.

  • Develop software components and APIs that enable seamless AI-assisted engineering processes and knowledge retrieval.

• Knowledge Management and Engineering Enablement

  • Collaborate with Design teams to capture, structure, and transform engineering knowledge into reusable AI-powered solutions.

  • Develop intelligent knowledge management systems that improve access to specifications, design documentation, best practices, and technical expertise.

  • Drive the adoption of AI-assisted workflows that enhance productivity, decision-making, and engineering quality.

• Product Design and Cross-Functional Collaboration

  • Partner with Product Design teams to integrate AI capabilities into product development processes, improving user experience, functionality, and engineering outcomes.

  • Collaborate with cross-functional stakeholders to identify and implement AI-driven solutions that support operational efficiency, innovation, and business growth.

  • Act as a trusted advisor and technical leader for AI initiatives across the organization.

• Vendor and Project Management

  • Manage external AI vendors, technology partners, and consultants, ensuring project delivery aligns with technical requirements, business objectives, timelines, and budgets.

  • Coordinate AI implementation projects from concept through deployment and operational support.

  • Assess vendor solutions and recommend build-versus-buy strategies for AI capabilities.

• Governance, Compliance, and Responsible AI

  • Establish and enforce AI governance frameworks, standards, and best practices.

  • Ensure AI solutions comply with security, privacy, regulatory, and ethical requirements.

  • Monitor AI system performance, reliability, safety, and risk management throughout the solution lifecycle.

• Training and AI Adoption

  • Provide training, mentoring, and technical guidance on AI technologies, applications, and best practices.

  • Promote AI literacy and foster a culture of AI-driven innovation within the Design organization.

  • Support teams in adopting AI tools and integrating them into daily engineering workflows.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Electrical Engineering, or a related field.

• Experience developing and deploying AI solutions using LLMs, RAG architectures, AI agents, and automation frameworks.

• Strong software engineering and system architecture experience, including cloud and infrastructure deployment.

• Knowledge of knowledge management systems, vector databases, APIs, and AI integration patterns.

• Experience working with engineering environments, EDA tools, or semiconductor design workflows is highly desirable.

• Proven ability to manage vendors and drive cross-functional technical initiatives.

• Strong communication, leadership, and stakeholder management skills.

• Understanding of AI governance, security, privacy, and responsible AI principles.

Success Measures

• Successful deployment and adoption of the Design Department's AI Operating System.

• Increased engineering productivity through AI-assisted workflows and automation.

• Improved accessibility and utilization of engineering knowledge assets.

• Effective integration of AI capabilities with existing design tools and processes.

• Compliance with governance, security, and responsible AI standards.

All applications will be treated in strict confidence and for recruitment purpose only.