✦ Luna Orbit — AI & Machine Learning

AI Engineer / Architect-IFS Cloud

at Rockwell Automation

📍 Milwaukee, Wisconsin, United States Hybrid Posted March 13, 2026
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves architecting and deploying advanced Generative AI and Agentic AI solutions, focusing on RAG pipelines, large language models, and scalable cloud infrastructure.

  • Design and deploy Agentic AI systems
  • Engineer RAG pipelines
  • Lead MLops infrastructure
  • Optimize model performance
  • Ensure secure AI architecture

The technical environment includes Generative AI, LLMs, RAG pipelines, MLops, Azure and Google cloud tools, Docker, vector databases, and system security.

The ideal candidate is an experienced AI/ML engineer with expertise in Generative AI, RAG pipelines, and cloud-native deployment using Azure and Google tools. They have a strong background in system architecture, performance optimization, and deploying large language models.

Experience with Generative AIRAG pipeline engineeringMLops infrastructurecloud-native deploymentLLM implementation
Semantic KernelAzure AI FoundryGoogle ADKvector database managementperformance tuning
Azure Machine LearningKubeflowDockerAzure OpenAIGoogle ADKvector databasesNoSQL databases
Generative AILLMRAG pipelinesMLopsAzure Machine LearningKubeflowDockervector databasesembeddingsAzure OpenAI
AIArtificial IntelligenceGenerative AILLMLarge Language ModelsRAG pipelinesRetrieval-Augmented GenerationMLopsAzure Machine LearningKubeflowDockervector databasesNoSQL databasesembeddingsAzure OpenAIGemini embeddingsperformance optimizationsystem architecturesecurity
leadershipproblem-solvingcollaborationcommunicationinnovative thinking
Industry Manufacturing, Industrial Automation, AI/ML
Job Function AI/ML engineering and system architecture for Generative AI
Generative AILLMLarge Language ModelsRAG pipelinesRetrieval-Augmented GenerationMLopsAzure Machine LearningKubeflowDockervector databasesNoSQL databasesembeddingsAzure OpenAIperformance optimizationsystem architecturecloud-native deployment

Lack of experience with Generative AI or LLMs, No background in cloud-native ML deployment, Unfamiliarity with RAG pipelines, No experience with MLops tools

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