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Koch Industries

Private conglomerate in energy and materials

AI Architect

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Experience designing and deploying artificial intelligence and machine learning and generative artificial intelligence solutions on modern cloud platforms such as Azure AI, Azure OpenAI, AWS Bedrock, SageMaker, Claude Code, Claude Cowork, or comparable platforms.
  • Working knowledge of core generative artificial intelligence building blocks, including large language models, prompt engineering, retrieval-augmented generation, embeddings, and vector stores.
  • Proven experience communicating artificial intelligence and technology concepts in execution detail and broad terms to technical and business audiences.
  • Demonstrated capability partnering with customers to understand business and operating models and translate them into artificial-intelligence-enabled solution proposals.
  • Experience in information technology, including hands-on delivery of data, analytics, or artificial intelligence and machine learning solutions.

Responsibilities

  • Partner with Product and business teams to identify high-value artificial intelligence and generative artificial intelligence use cases, then lead the technical solutioning process to build detailed architecture for how artificial intelligence will solve the problem.
  • Consider the enterprise picture as part of artificial intelligence solution design to produce reference architectures and patterns consistent with the information technology technical vision, data strategy, and responsible artificial intelligence standards.
  • Leverage expertise across multiple technical domains as part of the solutioning process, including machine learning, generative artificial intelligence and large language models, data engineering, security, cloud infrastructure, and application integration.
  • Lead the development and alignment of artificial intelligence architecture strategy, patterns, and guardrails across the engineering and design organization.
  • Identify, prototype, and evaluate emerging artificial intelligence models, agentic frameworks, and tooling to solve problems new to the organization.
  • Establish and champion responsible artificial intelligence practices, including model governance, security, data privacy, evaluation, and ongoing monitoring of solutions in production.
  • Execute on initiatives as appropriate.

Desired Qualifications

  • Experience supporting discrete engineering and manufacturing.
  • Experience designing and deploying agentic artificial intelligence, including conversational and action-oriented artificial intelligence agent platforms, to solve business problems.
  • Deep understanding of generative artificial intelligence and large language model architecture, including transformer models, fine-tuning, retrieval-augmented generation, embeddings, and prompt and context engineering.
  • Experience operationalizing artificial intelligence through large language model operations and machine learning operations practices for model deployment, evaluation, prompt and version management, monitoring, and drift detection.
  • Experience with vector databases and retrieval systems such as Azure AI Search, pgvector, and Pinecone.
  • Experience with artificial intelligence orchestration and agent frameworks such as LangChain, LlamaIndex, Semantic Kernel, and AutoGen.
  • Familiarity with responsible artificial intelligence and artificial intelligence governance, including safety, guardrails, bias mitigation, data privacy, and emerging regulatory requirements.
  • Experience with data architecture that supports artificial intelligence, including data lakes, graph and knowledge-graph technology, feature stores, and data pipelines.
  • Technical experience with serverless and event-driven cloud services, microservices, and containers, including Lambda, Azure Functions, SQS, SNS, EventBridge, API Gateway, Docker, Kubernetes, AKS, and ECS.
  • Experience with DevOps and MLOps methodologies and tools, including continuous integration and continuous delivery, GitHub, and Azure DevOps.

About the Company

Koch Industries

Private conglomerate in energy and materials

Koch Industries is a large, private, diversified conglomerate that operates in energy, chemical processing, and manufacturing. It started from an innovation that turned heavy crude oil into gasoline and grew through long‑term investments rather than short‑term market moves. The company generates value by refining fuels and producing chemical products, and it operates Georgia-Pacific, a major maker of paper and building products. Its business model relies on reinvesting most earnings back into the company to fund steady, long‑term growth rather than paying out frequent dividends or seeking quick profits. Koch differentiates itself from many competitors by staying privately owned, which reduces pressure from public markets and enables longer‑range planning. The company’s goal is to build scale and durability across its holdings by sustainable, multi‑decade growth rather than rapid, episodic gains.

Company size
5,001-10,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$985.2M
Headquarters
Wichita, KS
Founded
1940

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