Best NanoTech
Website:
bestpeo.com
Company:
https://www.linkedin.com/company/best-nanotech
Seniority: Mid-Senior level
Industries: Semiconductor Manufacturing
Job details:
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
Click on Apply to know more.