Senior Director, AI NPD Platforms & Engineering Intelligence
$216,775.00 to $390,195.00
Apply (opens in a new tab)Senior Director, AI NPD Platforms & Engineering Intelligence
Posted 39 days ago
SENIORITY
Manager
SALARY
$216,775.00 to $390,195.00
About the role
- Analog design
- Digital design
- VerificationPhysical design
- Design automation
- Semiconductor manufacturing flows
- Experience leading complex cross-functional engineering organizations.
- Proven ability to influence executive leadership and drive organizational transformation.
- Preferred
- LLMsRetrieval-Augmented Generation (RAG)
- Multi-Agent Architectures
- Model Context Protocol (MCP)
- Workflow Orchestration Platforms
- Reinforcement LearningAI Copilots
- Knowledge Graphs
- Develop and execute the long term strategy for Agentic AI-enabled semiconductor product development.
- Create the roadmap for AI deployment across product planning, architecture, design, verification, physical implementation, characterization, test, reliability, applications, and documentation.
- Define the maturity model for AI-assisted, AI-enabled, and AI-native development methodologies.
- Establish objectives, success metrics, and business outcomes tied to engineering productivity and NPD execution.
- Build the Agentic Design Platform
- Lead creation of an enterprise Agentic AI framework supporting:
- Analog design agents
- Digital design agents
- Verification agents
- Layout agents
- Test engineering agents
- Applications engineering agents
- Documentation and requirements agents
- Program management agents
- Define standards for agent architecture, interoperability, orchestration, security, and lifecycle management.
- Partner with engineering, CAD, IT, and infrastructure teams to deploy scalable AI design environments.
- Govern AI Agents as Strategic IPEstablish companywide governance for AI agents and engineering knowledge assets.
- Develop processes for agent qualification, validation, release, version control, maintenance, retirement, and reuse.
- Create an "Agent Library" and corporate repository of approved agents, prompts, workflows, and design knowledge.
- Define review and approval processes for new internally developed agents.
- Ensure cross division reuse of agents.
- Transform Analog and Digital DesignDefine AI-enabled methodologies across:
- Circuit design
- Architecture explorationRTL development
- VerificationPhysical design
- Device characterization
- Design reviews
- Failure analysis
- Documentation generation
- Drive deployment of AI workflows into production engineering environments.
- Identify high-value use cases capable of delivering significant improvements in development cycle time, engineering efficiency, and design quality.
- Create the AI Governance Operating ModelDefine AI governance policies for engineering workflows.
- Establish standards for:
- Model selection
- Training data usage
- Intellectual property protection
- Security and access controls
- Human-in-the-loop decision processes
- Validation requirements
- Auditability and traceability
- Ensure responsible deployment of AI systems across engineering organizations.
- Drive Measurable Business Outcomes
- Establish KPI frameworks measuring:
- NPD cycle time
- Design productivity
- Engineering efficiency
- Agent reuse ratesAI adoption
- Design quality improvements
- Verification coverage improvementsIP creation velocity
- Deliver measurable improvements in development throughput and engineering effectiveness.
- Full time
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
