BN
AI Solutions Architect – Semiconductor Enablement & Engineering Automation
Accepting applicationsBest NanoTech · Bengaluru, Karnataka, India
Full-Time Mid_senior AIASICC++DFTDeep Learning
Estimated market salary
₹21-38 LPA
This is a SiliconBoard market estimate, not an employer-posted salary.
Posted
1d ago
Category
Manufacturing
Experience
Mid_senior
Country
India
AI Solutions Architect Semiconductor Enablement & Engineering Automation
Location: Bengaluru, India
Work Mode: Onsite / Hybrid
Experience: 10 18 Years
Industry: Semiconductor | Artificial Intelligence | EDA | Digital Engineering
Role Overview
We are seeking an experienced AI Solutions Architect to lead the adoption of Artificial Intelligence and Machine Learning across semiconductor engineering, design enablement, and manufacturing workflows. This role focuses on building AI-driven solutions that improve engineering productivity, automate complex design processes, optimize semiconductor development cycles, and accelerate decision-making across chip design, verification, technology development, and manufacturing.
The ideal candidate combines strong expertise in AI/ML technologies, semiconductor design flows, EDA tools, data engineering, cloud platforms, and software architecture, with the ability to collaborate across engineering, product, and manufacturing teams to deliver scalable AI solutions.
Key Responsibilities
Define and execute AI strategy supporting semiconductor engineering and technology development.
Design and deploy AI/ML solutions for chip design, verification, process optimization, yield analysis, and engineering automation.
Develop AI frameworks to improve RTL development, DFT, Physical Design, timing analysis, verification, and manufacturing analytics.
Collaborate with semiconductor design, CAD, EDA, manufacturing, and data engineering teams to identify automation opportunities.
Build AI-powered engineering assistants, knowledge management platforms, and decision-support systems.
Develop scalable data pipelines integrating engineering databases, simulation results, manufacturing data, and design repositories.
Evaluate and integrate Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and AI agents into engineering workflows.
Architect cloud-native AI platforms supporting secure and scalable semiconductor development environments.
Lead AI governance, model lifecycle management, security, and responsible AI implementation.
Mentor engineering teams and establish AI best practices across the organization.
Drive proof-of-concept projects through production deployment while measuring business impact.
Collaborate with global engineering teams, customers, and technology partners on AI-enabled semiconductor solutions.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Electronics Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or a related field. Ph.D. is a plus.
10 18 years of experience in software engineering, AI/ML, semiconductor engineering, or digital transformation.
Proven experience architecting enterprise-scale AI solutions.
Strong understanding of semiconductor design, manufacturing, or EDA workflows.
Technical Skills Artificial Intelligence
Machine Learning
Deep Learning
Generative AI
Large Language Models (LLMs)
AI Agents
Retrieval-Augmented Generation (RAG)
Prompt Engineering
AI Model Deployment
Semiconductor Enablement
Semiconductor Design Flow
ASIC / SoC Development
Physical Design
RTL Design
Design Verification
DFT
CAD Automation
Yield Analytics
Manufacturing Analytics
Programming
Python
C++
Java
SQL
APIs
REST Services
AI Frameworks
PyTorch
TensorFlow
Hugging Face
LangChain
LlamaIndex
MLflow
Vector Databases
Cloud & Infrastructure
AWS
Microsoft Azure
Google Cloud Platform
Kubernetes
Docker
MLOps
CI/CD
Data Engineering
Data Pipelines
Spark
Kafka
Snowflake
Databricks
Data Lakes
ETL
#LI-SD1
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Location: Bengaluru, India
Work Mode: Onsite / Hybrid
Experience: 10 18 Years
Industry: Semiconductor | Artificial Intelligence | EDA | Digital Engineering
Role Overview
We are seeking an experienced AI Solutions Architect to lead the adoption of Artificial Intelligence and Machine Learning across semiconductor engineering, design enablement, and manufacturing workflows. This role focuses on building AI-driven solutions that improve engineering productivity, automate complex design processes, optimize semiconductor development cycles, and accelerate decision-making across chip design, verification, technology development, and manufacturing.
The ideal candidate combines strong expertise in AI/ML technologies, semiconductor design flows, EDA tools, data engineering, cloud platforms, and software architecture, with the ability to collaborate across engineering, product, and manufacturing teams to deliver scalable AI solutions.
Key Responsibilities
Define and execute AI strategy supporting semiconductor engineering and technology development.
Design and deploy AI/ML solutions for chip design, verification, process optimization, yield analysis, and engineering automation.
Develop AI frameworks to improve RTL development, DFT, Physical Design, timing analysis, verification, and manufacturing analytics.
Collaborate with semiconductor design, CAD, EDA, manufacturing, and data engineering teams to identify automation opportunities.
Build AI-powered engineering assistants, knowledge management platforms, and decision-support systems.
Develop scalable data pipelines integrating engineering databases, simulation results, manufacturing data, and design repositories.
Evaluate and integrate Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and AI agents into engineering workflows.
Architect cloud-native AI platforms supporting secure and scalable semiconductor development environments.
Lead AI governance, model lifecycle management, security, and responsible AI implementation.
Mentor engineering teams and establish AI best practices across the organization.
Drive proof-of-concept projects through production deployment while measuring business impact.
Collaborate with global engineering teams, customers, and technology partners on AI-enabled semiconductor solutions.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Electronics Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or a related field. Ph.D. is a plus.
10 18 years of experience in software engineering, AI/ML, semiconductor engineering, or digital transformation.
Proven experience architecting enterprise-scale AI solutions.
Strong understanding of semiconductor design, manufacturing, or EDA workflows.
Technical Skills Artificial Intelligence
Machine Learning
Deep Learning
Generative AI
Large Language Models (LLMs)
AI Agents
Retrieval-Augmented Generation (RAG)
Prompt Engineering
AI Model Deployment
Semiconductor Enablement
Semiconductor Design Flow
ASIC / SoC Development
Physical Design
RTL Design
Design Verification
DFT
CAD Automation
Yield Analytics
Manufacturing Analytics
Programming
Python
C++
Java
SQL
APIs
REST Services
AI Frameworks
PyTorch
TensorFlow
Hugging Face
LangChain
LlamaIndex
MLflow
Vector Databases
Cloud & Infrastructure
AWS
Microsoft Azure
Google Cloud Platform
Kubernetes
Docker
MLOps
CI/CD
Data Engineering
Data Pipelines
Spark
Kafka
Snowflake
Databricks
Data Lakes
ETL
#LI-SD1
Show more Show less