Key Responsibilities
AI Agent Development: Build and optimize AI agents using LLMs, MCPs, Skills and RAG to develop tools for FPGA solutions.
User Interface Creation: Design and implement modern, responsive UIs to visualize FPGA data and provide a seamless interface for interacting with AI-driven tools.
System Integration: Integrate AI backends with user-facing applications, ensuring high reliability and a fluid user experience for hardware engineering teams.
Technical Guidance: Provide expertise on the intersection of AI and hardware tooling, setting the standard for software quality and innovation within the team.
Technical Qualifications
Experience: Hands-on development experience in software and AI engineering, with a focus on building complex tools, platforms, or automation systems. Experience in productizing SW tools.
AI/ML Expertise: Strong proficiency in the LLM application stack, including prompt engineering, vector databases, and agentic frameworks (e.g., LangChain).
Frontend Development: Skills in modern Python/JavaScript frameworks (React, Vue, Next.js, or PyQT framework) and styling libraries.
Programming Languages: Deep knowledge of Python for backend and AI logic; familiarity with Node.js or similar environments.
Domain Awareness: An FPGA background is preferable but not a must. You must demonstrate the ability to quickly master complex technical domains. Familiarity with hardware design flows or EDA tools is a significant advantage.
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