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)

Positive 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

📌 AI Platform Architect (Semiconductor Design) (Bengaluru)
🏢 Virtual Connect Solutions
📍 Bengaluru