Sr. Software Engineer - AI/ML

Company Overview

KLA 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/Division

The 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

Our Enterprise Analytics & Data Science team 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 a collaborative, cross-functional group of engineers, data scientists, analysts, and architects. You’ll be joining a team that believes in building 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 scalable patterns for LLM apps, MLOps, and data products.

• Owns operational excellence (monitoring, reliability, security, compliance) for AI services in production.

• Mentors others and raises the bar through reviews, standards, and knowledge sharing.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).

• Minimum eight (8) years experience in software