About This Role
This AI Solutions Engineer role focuses on transforming semiconductor debugging and tool readiness through AI-powered solutions. The person in this role will work with debug tools developers, architects, and SoC engineers to identify high-impact engineering problems and rapidly develop AI-driven solutions that improve productivity, accelerate bring-up activities, and shift-left debug readiness.
Responsibilities
- Partner with debug tools leads, debug teams, and key users to identify engineering bottlenecks and automation opportunities
- Design, prototype, and deploy AI-powered solutions that improve debug efficiency, reduce manual effort, and accelerate root-cause analysis
- Develop agentic workflows, copilots, MCP integrations, RAG systems, and AI assistants for semiconductor debugging use cases
- Build proof-of-concepts and production-ready solutions using LLMs, AI agents, and automation frameworks
- Translate semiconductor debug workflows into scalable software and AI solutions
- Analyze logs, reports, register data, validation results, and other engineering artifacts to develop intelligent troubleshooting capabilities
- Drive shift-left initiatives by enabling earlier defect detection, readiness validation, and automated diagnostics
- Work closely with software, firmware, validation, and silicon teams to deploy solutions into daily engineering workflows
- Measure business impact through productivity improvements, cycle-time reduction, and readiness acceleration
- Evangelize AI best practices and help engineers adopt AI-first workflows
Requirements
- Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field
- 5-8 years of software engineering, automation, validation, or semiconductor engineering experience
- Strong programming skills in Python
- Experience developing enterprise applications, automation solutions, or engineering tools
- Hands-on experience with Generative AI technologies including:
- LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.)
- Agentic AI frameworks
- MCP (Model Context Protocol)
- Retrieval Augmented Generation (RAG)
- Vector databases and embeddings
- Prompt engineering and evaluation
- Experience building APIs, automation workflows, and integrations
- Strong analytical and problem-solving skills
- Excellent communication and stakeholder management abilities
Nice to have:
- Experience in semiconductor debugging, silicon validation, bring-up, or DFT/debug environments
- Familiarity with scan, JTAG, registers, validation logs, silicon debug, or post-silicon workflows
