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Senior AI Architect

On site · Contract · On site

Senior AI Architect

Location:  Denver, CO OR Minneapolis, MN (Hybrid)
Duration:  12 Month contract to hire
Pay:  $125/hr

W2 ONLY, NO C2C

Quick summary: 
The Senior AI Architect designs and delivers scalable, secure AI solutions aligned to enterprise strategy and standards. This role combines hands on technical leadership with architectural guidance, partnering closely with data, platform, security, and application teams to integrate AI capabilities into core business systems. The Senior AI Architect contributes to solution design, supports implementation teams, and helps mature enterprise AI platforms, patterns, and governance.

Core AI & ML Skills
  • Designing and implementing production AI and GenAI solutions (including LLM‑based systems)
  • Hands‑on experience with AI model development, prototyping, and deployment
  • Understanding of ML lifecycle concepts including training, inference, evaluation, and iteration
AI Architecture & Platform Design
  • Architecture design for scalable, reliable AI platforms and services
  • Applying AI architecture patterns, standards, and guardrails aligned to enterprise strategy
  • Experience integrating AI capabilities into existing enterprise systems and workflows
Engineering & Implementation Skills
  • Strong collaboration with engineering teams to design, build, and optimize AI solutions
  • Ability to move from conceptual design to working implementations (hands‑on delivery focus)
  • Familiarity with cloud‑native architectures and modern development practices
Data & Integration Foundations
  • Solid understanding of data pipelines, data platforms, and data quality considerations supporting AI workloads
  • Experience designing AI solutions that depend on enterprise data assets and analytics platforms
Governance, Risk & Enterprise Alignment
  • Applying architectural standards, patterns, and principles consistently across solutions
  • Awareness of AI risks including model performance, bias, explainability, and operational robustness
  • Ability to align AI solutions to enterprise technology strategy and business outcomes
Communication & Collaboration
  • Translating complex AI concepts into clear architecture guidance for delivery teams and stakeholders
  • Partnering effectively across data, platform, security, and application teams
  • Contributing to roadmap discussions and technical decisions without owning full domain governance (as Principal would)

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