AI-First Data Solutions Architect

Koch

Plano (TX)

On-site

USD 140,000 - 190,000

Full time

2 days ago

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Job summary

Koch Technology Data Solutions (KTDS) is seeking a Data & AI Solutions Architect to shape data, analytics, automation, and AI across Koch. You will translate business outcomes into scalable architectures, guide technology choices, and accelerate delivery with reusable patterns.

The ideal candidate embraces AI as a core capability and rapidly prototypes solutions while ensuring governance and responsible AI practices.

Qualifications

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.

Responsibilities

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.