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AI Software Engineer - Operations

Job in Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listing for: KLA-Belgium
Full Time position
Listed on 2026-09-04
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Backend Developer, Full Stack Developer
Salary/Wage Range or Industry Benchmark: 90000 - 154000 USD Yearly USD 90000.00 154000.00 YEAR
Job Description & How to Apply Below

Company Overview

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.

Job Description /Preferred Qualifications

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., Lang Chain, Semantic Kernel, Llama Index)
  • 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 delivering production-grade AI solutions
  • Familiarity with prompt engineering and LLM interaction patterns
  • Experience developing web-based user interfaces (e.g., React, Angular, or similar frameworks)
  • Experience working in with or for a global manufacturing…
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