To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale-faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology. Group/DivisionKLA has manufacturing sites worldwide. The Global Operations (GOPS) team, comprised of Manufacturing, Supply Chain Management, Manufacturing Engineering, Installation and Quality, builds our leading-edge technology. GOPS partners with KLA's global supply base and design engineering teams to develop new products, working continuously to build better, faster and more cost-efficient solutions. What You'll Do In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise. The AI Software Engineer will design and build AI-driven applications powered by large language models (LLMs), with a focus on integrating AI capabilities into user-facing products. This role emphasizes application development, orchestration, and user experience rather than model training. The engineer will develop scalable backend services, prototype intuitive user interfaces, and enable seamless interaction between users and LLM-based systems. This position requires a strong blend of software engineering, systems thinking, and practical AI implementation to deliver production-ready solutions that leverage LLM APIs and frameworks.Design and develop end-to-end AI applications that leverage LLMs for business use cases Responsibilities: Build and maintain backend services that orchestrate LLM interactions, prompts, and workflows Prototype and develop intuitive user interfaces that enable effective human-AI interaction Integrate LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) into scalable applications Develop prompt engineering strategies and manage prompt lifecycle for performance and reliability Implement retrieval-augmented generation (RAG) architectures using internal and external data sources Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge bases) Monitor, evaluate, and improve AI application performance using metrics such as latency, cost, and response quality Collaborate with product managers, data scientists, and business stakeholders to translate requirements into AI-enabled solutions Ensure responsible AI practices, including privacy, security, and bias mitigation Rapidly prototype AI tools and iterate based on user feedback Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or related field Minimum three (3) years of professional software development experience Strong programming skills in Python, JavaScript, or similar languages Experience building AI products using LLM frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex) Knowledge of retrieval-augmented generation (RAG) and vector databases (e.g., Pinecone, FAISS, Azure Cognitive Search) Vector database (Milvus) for semantic search, along with a knowledge graph (Neo4j) Experience orchestrating multi-step AI workflows or agent-based systems Familiarity with enterprise data platforms and integrations (e.g., Snowflake, SAP, APIs, knowledge graphs) Experience designing conversational interfaces or chat-based applications Understanding of evaluation techniques for LLM outputs (quality, grounding, hallucination mitigation) Exposure to prompt optimization, fine-tuning concepts (not necessarily hands-on training) Experience deploying scalable microservices architectures Strong UI/UX sensibility for AI-driven applications Experience working in cross-functional teams d