AI Agent Engineer

About the role

Design, build, and optimize domain-specific AI agents across multiple areas such as semiconductor design, semiconductor manufacturing, and internet products. Own the end-to-end lifecycle of AI agents, including requirement discovery, agent architecture design, tool integration, and continuous iteration based on user feedback.

Key responsibilities

• Design multi-step reasoning flows, integrating external tools and APIs
• Conduct prompt and policy optimization, and implement evaluation strategies to measure task success, safety, and reliability
• Work with LLM platforms, retrieval-augmented generation (RAG), and orchestration frameworks
• Translate complex business and engineering use cases into practical AI agent solutions
• Collaborate closely with domain experts to encode workflows and best practices into robust, reliable agentic systems
• Connect agents to external tools, databases, and enterprise APIs (e.g., EDA tools in chip design, CRM, internal microservices)
• Implement multi-agent coordination and complex workflow automation
• Design robust evaluation strategies: task success metrics, safety guardrails, reliability benchmarks, and user feedback loops

About you

• Strong understanding of agentic systems, including planning, reasoning, memory, tool use, and reflection mechanisms
• Experience designing modular, scalable, and maintainable agent architectures for domain-specific applications
• Hands-on experience with commercial and open-source LLMs
• Proficiency in prompt engineering, chaining, and policy design to guide agent behavior
• Expertise in building RAG pipelines: document ingestion, embedding, vector search, context fusion, and answer generation
• Ability to optimize retrieval relevance and mitigate hallucination in domain contexts (e.g., semiconductor or internet product data)
• Skilled at connecting agents to external tools, databases, and enterprise APIs
• Experience with agent orchestration platforms such as LangChain, LlamaIndex, Semantic Kernel, or custom frameworks
• Capable of designing robust evaluation strategies and data-driven mindset for continuous agent improvement and A/B testing
• Solid coding skills in Python