AI Platform Architect (Semiconductor Design)

We are looking for a highly capable AI Engineer / AI Platform Architect who will define and drive our AI strategy, infrastructure, and agent-based workflows for semiconductor design. This role sits at the intersection of AI, EDA, and engineering productivity, and will be instrumental in transforming how chips are built.

What You’ll Do

AI Strategy & Vision

Define and execute the AI roadmap for semiconductor design workflows across:
Architecture
RTL design
Verification
Physical design
Analog design
Identify high-impact opportunities where AI can significantly improve:
Productivity
Quality
Time-to-silicon
Serve as the central thought leader for AI adoption across the company

AI Infrastructure & Platform

Architect and deploy AI infrastructure, including:
Cloud-based (e.g., AWS) and/or on-prem (air-gapped) environments
GPU/compute resource planning and scaling
Define strategy for:
Model hosting vs API usage
Offline/private model deployment for IP-sensitive environments
Build systems for:
Data management, protection, and governance
IP security and compliance
Auditability and traceability of AI-generated outputs

AI Agents & Workflow Automation

Work closely with engineering teams to:
Identify workflows suitable for AI agent automation
Define multi-step agent pipelines spanning different tools and domains
Design and implement AI agents that can:
Interact with EDA tools
Execute multi-stage workflows (e.g., generate → simulate → analyze → refine)
Integrate across RTL, DV, and physical design flows
Build reusable agent frameworks and orchestration layers

AI Guardrails & Governance

Define and enforce AI guardrails, including:
Safe usage policies
Data privacy and IP protection
Model access controls
Manage:
Token usage and cost optimization
Access policies for different teams
Ensure AI usage aligns with enterprise-grade security standards

LLM & Tooling Expertise

Evaluate and recommend LLMs and AI tools for different use cases:
Code generation
Debugging
Documentation
Data analysis
Continuously benchmark and optimize model selection across:
Performance
Cost
Privacy constraints
Stay current with advancements in:
LLMs
Agent frameworks
AI tooling ecosystem

Enablement & Training

Train engineering teams to:
Effectively use AI tools and agents
Build their own custom AI agents
Apply prompt engineering best practices
Create documentation, playbooks, and templates for:
AI-assisted workflows
Agent development
Drive a culture of AI-native engineering

What We’re Looking For

Bachelor’s/Master’s/PhD in Computer Science, Electrical Engineering, or related field
8+ years of experience in AI/ML, systems, or platform engineering
Strong experience in:
LLMs and generative AI systems
Building AI-powered tools or platforms
Designing scalable AI infrastructure (cloud and/or on-prem)
Experience with:
Agent frameworks and orchestration systems
API-based and self-hosted models
Solid understanding of:
Data security, privacy, and IP protection in AI systems
Strong software engineering skills (Python required)

Good to Have

Experience working with semiconductor or EDA workflows
Familiarity with:
RTL, verification, or physical design flows
Experience with:
Air-gapped or secure AI deployments
GPU clusters and distributed training/inference
Knowledge of:
Prompt engineering techniques
Retrieval-augmented generation (RAG)
Workflow automation systems
Exposure to DevOps / MLOps practices

Skills: llm,ai/ml,design,semiconductor
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