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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data & AI Solutions Architect - **Company:** Koch, Inc. - **Location:** Wichita, KS, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Cloud Engineering, Graph Database, Data Logging, Retrieval-Augmented Generation, Snowflake, Generative AI, Agentic-AI, Data Layers, Microsoft Fabric, AI Platforms, Data Management, Api Design - **Published:** November 8, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-ai-solutions-architect-wichita-ks--05ec05b9-e2fb-4a06-beeb-2c23bb6646e6 ## About the Role Artificial Intelligence (AI), Artificial Intelligence (AI), English Language, Facebook, LinkedIn, Automation, Data Analysis, Prototyping, Process Improvement, Automation Systems, * Experience translating business outcomes into scalable Data & AI architectures and influencing technical direction across teams. * Experience designing end-to-end Data & AI solutions using cloud, data, and AI platforms such as AWS, Snowflake, Microsoft Fabric, or similar technologies. * Experience advancing platform adoption through product management, developer enablement, or adoption metrics. * Experience using AI and AI-DLC practices to accelerate solution design, planning, delivery, and decision-making. * Demonstrated ability to create architecture artifacts and build prototypes, reference implementations, or technical evaluations that validate decisions and reduce delivery risk. * Demonstrated understanding of architecture and responsible AI principles, including security, privacy, governance, observability, resiliency, and supportability; paired with strong stakeholder management and influence skills. What Will Put You Ahead * Experience defining and scaling enterprise Data & AI platform strategies, operating models, and shared capabilities across multiple domains. * Experience applying modern architecture principles, including cloud-native, API-first, event-driven, and domain-oriented design, as well as AI-enabled workflows, generative AI, agentic AI, and RAG solutions. * Experience using ontologies, knowledge graphs, semantic layers, or knowledge-based architectures. * Experience scaling AI-assisted engineering practices that improve productivity, quality, reliability, or delivery speed. * Hands-on experience building or operating Model Context Protocol (MCP) servers or similar standards for connecting AI agents to enterprise systems. * Experience mentoring architects and technical resources to improve architectural decision-making and consistency. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate''s knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy. ## Description * Employee Login * Home * Search Jobs * Life at Koch * Companies * Career Opportunities * How We Hire * Early Careers * Recruiting Events * Candidate Portal * Join our Talent Community * Employee Login * Learn More About Koch * Latest Koch News * English - US * Deutsch * English - US * Español - ES * Français - France * Polski, * Partner with stakeholders to understand business outcomes and translate them into scalable Data & AI architectures. * Develop solution designs, architecture standards, and implementation guidance that promote consistency, reuse, and delivery speed. * Build alignment and influence decisions across business, product, engineering, security, governance, and platform teams. * Design end-to-end data and AI solutions spanning data platforms, integrations, analytics, automation, governance, and AI capabilities. * Apply cloud-native, API-first, event-driven, and domain-oriented design principles. * Identify opportunities where AI can improve decision-making, productivity, operations, and business outcomes. * Establish architecture patterns, standards, and guardrails that enable secure, scalable, resilient, and supportable solutions. * Apply Harness Engineering principles to embed governance and standards into delivery workflows. * Leverage AI and AI-DLC practices to accelerate solution exploration, architecture, planning, documentation, and delivery while maintaining ownership of recommendations. * Build and evaluate prototypes, reference implementations, agentic workflows, and technical spikes to validate approaches and reduce risk. * Champion responsible AI practices, including security, privacy, governance, observability, evaluation, and human oversight., * Strictly Necessary Cookies Strictly Necessary Cookies Always Active Strictly Necessary Cookies These cookies are necessary for the website to function and cannot be switched off in our systems. 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