AI Organizational Architect

Basic Function

Lumin Digital is hiring a Staff AI Organizational Architect to own the technical strategy for how we use AI across the company. This is a senior individual contributor role responsible for bringing clarity and accountability to Lumin's growing AI investment: understanding where AI is creating genuine value, reducing what isn't working, and helping the company scale what is. The right person will sit at the intersection of hands-on technical depth and enterprise-level advisory work, serving as a trusted resource for executives, engineering teams, and cross-functional partners including Risk, Compliance, and Legal. Success in this role means Lumin's AI spend is better understood, better directed, and more consistently tied to business outcomes.

Essential Functions and Responsibilities:

• Define and continuously evolve Lumin's internal AI technical strategy, including evaluation of models, vendors, platforms, frameworks, and deployment architectures against criteria of capability, cost, reliability, security, and business fit.

• Build and maintain clear visibility into AI usage, adoption, and spend across the enterprise; help leaders connect AI investment to meaningful business outcomes and identify where spend should be reduced or increased.

• Serve as a trusted technical advisor to executives, business leaders, and engineering teams evaluating AI use cases, experiments, and implementation approaches.

• Help successful AI experiments become repeatable, supportable capabilities; distinguish productive experimentation from work unlikely to create sufficient value.

• Partner with Risk, Compliance, and Legal to evolve Lumin's approach to responsible AI use, including establishing practical standards, decision rights, review processes, and escalation paths.

• Own a defined cadence of reviews for AI platforms, models, configurations, and controls; maintain current awareness of emerging risks and capabilities.

• Establish and communicate Lumin's internal AI standards, reference architectures, and recommended technologies; provide consistent, technically credible guidance to the organization.

• Challenge weak assumptions, unnecessary complexity, and poor technology choices across teams; translate rapidly changing AI capabilities into practical recommendations.

• Personally evaluate AI models, APIs, and frameworks through direct implementation. Not just vendor briefings or architectural review.

• Prototype and validate new AI capabilities before recommending them for broader adoption; own the technical risk assessment through working code, not just documentation.