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AI Platform Architect - Semiconductor Design
Accepting applicationsNetConnect AS · Bengaluru, Karnataka, India
Full-Time Senior Machine LearningAIPythonSemiconductor DesignEDA
Estimated market salary
₹28-50 LPA
This is a SiliconBoard market estimate, not an employer-posted salary.
Posted
3d ago
Category
Design
Experience
Senior
Country
India
About The Role
We are looking for a highly experienced AI Engineer / AI Platform Architect to lead the adoption of Artificial Intelligence across our semiconductor design organization. This is a strategic and hands-on leadership role that combines AI, platform engineering, and semiconductor workflows to transform how chips are designed, verified, and delivered.
You will define the company's AI roadmap, build scalable AI infrastructure, develop agent-based automation systems, and enable engineering teams to leverage AI securely and effectively across RTL design, verification, physical design, and architecture workflows.
This role offers a unique opportunity to shape the future of an AI-native semiconductor company.
Key Responsibilities
AI Strategy & Transformation :
Define and drive the company-wide AI vision and roadmap for semiconductor engineering workflows.
Identify high-impact AI use cases across :
Chip Architecture
RTL Design
Design Verification
Physical Design
Analog/Mixed-Signal Design
Deliver measurable improvements in :
Engineering productivity
Design quality
Time-to-silicon
Workflow automation
Serve as the technical leader influencing AI adoption across engineering teams.
AI Infrastructure & Platform Engineering
Design and deploy enterprise-grade AI platforms in cloud and on-premise environments.
Architect secure AI environments including :
AWS/Azure/GCP
Private deployments
Air-gapped environments
GPU infrastructure
Define AI deployment strategy, including :
Hosted APIs vs self-hosted models
Open-source vs commercial LLMs
Model serving and scaling
Build frameworks for :
Data governance
IP protection
Security and compliance
Auditability and traceability
AI Agents & Workflow Automation
Partner with semiconductor engineering teams to automate complex workflows using AI agents.
Design and implement agentic systems that can :
Interact with EDA tools
Execute multi-step workflows
Analyze simulation and verification results
Generate recommendations and refinements
Develop reusable agent frameworks and orchestration layers.
Enable automation across RTL, DV, Physical Design, and architecture flows.
LLM Evaluation & Optimization
Evaluate and benchmark modern AI models for engineering use cases.
Recommend the right model based on :
Performance
Cost
Privacy requirements
Latency
Drive adoption of AI solutions for :
Code generation
Debugging
Documentation
Knowledge management
Engineering productivity
AI Governance & Security
Establish AI usage policies, standards, and governance frameworks.
Implement controls for :
Data privacy
IP security
User access management
Model governance
Monitor and optimize :
AI consumption
Token usage
Infrastructure costs
Ensure compliance with enterprise security standards.
Enablement & Training
Train engineering teams on AI tools, agent development, and prompt engineering best practices.
Create playbooks, templates, and best practices for AI-assisted workflows.
Foster a culture of AI-native engineering and continuous innovation.
Required Qualifications
Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, AI/ML, or related field.
8+ years of experience in AI/ML, platform engineering, software engineering, or related domains.
Strong hands-on experience with :
Large Language Models (LLMs)
Generative AI applications
AI-powered platforms and products
Agentic AI systems
Expertise in Python and software engineering best practices.
Experience designing scalable cloud-based and/or on-prem AI infrastructure.
Strong understanding of :
Data privacy
Security
IP protection
Enterprise AI governance
(ref:hirist.tech)
Show more Show less
We are looking for a highly experienced AI Engineer / AI Platform Architect to lead the adoption of Artificial Intelligence across our semiconductor design organization. This is a strategic and hands-on leadership role that combines AI, platform engineering, and semiconductor workflows to transform how chips are designed, verified, and delivered.
You will define the company's AI roadmap, build scalable AI infrastructure, develop agent-based automation systems, and enable engineering teams to leverage AI securely and effectively across RTL design, verification, physical design, and architecture workflows.
This role offers a unique opportunity to shape the future of an AI-native semiconductor company.
Key Responsibilities
AI Strategy & Transformation :
Define and drive the company-wide AI vision and roadmap for semiconductor engineering workflows.
Identify high-impact AI use cases across :
Chip Architecture
RTL Design
Design Verification
Physical Design
Analog/Mixed-Signal Design
Deliver measurable improvements in :
Engineering productivity
Design quality
Time-to-silicon
Workflow automation
Serve as the technical leader influencing AI adoption across engineering teams.
AI Infrastructure & Platform Engineering
Design and deploy enterprise-grade AI platforms in cloud and on-premise environments.
Architect secure AI environments including :
AWS/Azure/GCP
Private deployments
Air-gapped environments
GPU infrastructure
Define AI deployment strategy, including :
Hosted APIs vs self-hosted models
Open-source vs commercial LLMs
Model serving and scaling
Build frameworks for :
Data governance
IP protection
Security and compliance
Auditability and traceability
AI Agents & Workflow Automation
Partner with semiconductor engineering teams to automate complex workflows using AI agents.
Design and implement agentic systems that can :
Interact with EDA tools
Execute multi-step workflows
Analyze simulation and verification results
Generate recommendations and refinements
Develop reusable agent frameworks and orchestration layers.
Enable automation across RTL, DV, Physical Design, and architecture flows.
LLM Evaluation & Optimization
Evaluate and benchmark modern AI models for engineering use cases.
Recommend the right model based on :
Performance
Cost
Privacy requirements
Latency
Drive adoption of AI solutions for :
Code generation
Debugging
Documentation
Knowledge management
Engineering productivity
AI Governance & Security
Establish AI usage policies, standards, and governance frameworks.
Implement controls for :
Data privacy
IP security
User access management
Model governance
Monitor and optimize :
AI consumption
Token usage
Infrastructure costs
Ensure compliance with enterprise security standards.
Enablement & Training
Train engineering teams on AI tools, agent development, and prompt engineering best practices.
Create playbooks, templates, and best practices for AI-assisted workflows.
Foster a culture of AI-native engineering and continuous innovation.
Required Qualifications
Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, AI/ML, or related field.
8+ years of experience in AI/ML, platform engineering, software engineering, or related domains.
Strong hands-on experience with :
Large Language Models (LLMs)
Generative AI applications
AI-powered platforms and products
Agentic AI systems
Expertise in Python and software engineering best practices.
Experience designing scalable cloud-based and/or on-prem AI infrastructure.
Strong understanding of :
Data privacy
Security
IP protection
Enterprise AI governance
(ref:hirist.tech)
Show more Show less