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Company OverviewKLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays.  The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Group/DivisionThe Information Technology (IT) group at KLA is involved in every aspect of the global business. IT's mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.

Job Description/Preferred Qualifications OurEnterprise Analytics & Data Scienceteam is at the forefront of transforming data into actionable insights that drive strategic decisions across the organization. You will be working on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines. You'll help design, build, and evaluate AI systems that solve complex real-world problems at scale. We are acollaborative, cross-functional groupof engineers, data scientists, analysts, and architects. You'll be joining a team that believes inbuilding with purpose, where engineering excellence meets data-driven strategy

Key Responsibilities:

Design and deliver LLM-powered applications such as:

Retrieval-Augmented Generation (RAG) with enterprise knowledge sources

Agentic workflows (tool/function calling, orchestration, multi-step reasoning)

Text extraction/summarization, classification, Q&A, and document intelligence

Build and optimize retrieval pipelines: chunking strategies, embeddings, vector search, reranking, grounding, and evaluation.

Implement safety and quality guardrails: prompt injection defenses, PII redaction, secure prompt templates, hallucination mitigation, and auditability.

Create robust evaluation frameworks: golden datasets, automated scoring, offline/online A/B testing, and continuous regression testing for prompts/models.

Lead technical design for complex initiatives; define reference architectures and reusable components for LLM applications and MLOps.

Mentor engineers, conduct design/code reviews, and elevate engineering standards (testing, documentation, observability, security).

Partner with stakeholders to translate ambiguous business needs into clear AI deliverables, milestones, success metrics, and operational SLAs.

Core Technical Skills:

LLM Apps: RAG, agents, tool/function calling, prompt engineering, evaluation harnesses, guardrails

Languages: Python (required), SQL (required)

Cloud: Azure (deployments, security, observability, CI/CD)

Ops: Monitoring, incident response, SLO/SLA management, cost optimization

Data: ETL/ELT, distributed processing concepts, data quality frameworks

Expectations:

Leads delivery for ambiguous, high-impact AI initiatives with minimal oversight.

Influences architecture and establishes scal