Lead Architect, Enterprise AI Platform & LLM

Information Technology Senior Management Forum; Irving (TX); Hybrid; USD 121,000 - 231,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Parental leave

Tuition assistance

Job summary

Verizon is seeking a Principal Architect for its Enterprise AI Platform to provide technical leadership across a 5-layer architecture serving global business units. You will drive architectural coherence, ADRs, ARB submissions, and rigorous build-vs-buy analyses with multi-year TCO models.

This role requires deep LLM expertise, enterprise-scale Kubernetes, and cross-functional collaboration with executives and engineering teams to shape the future of AI platforms.

Qualifications

• Proven history of designing scalable distributed platforms with ADRs.
• Strong ability to substantiate build-vs-buy recommendations with 3-year TCO models.
• Experience presenting architecture recommendations to VP/SVP-level leadership.

Responsibilities

• Direct the 5-layer architecture stack and define layer boundaries, interfaces and interaction patterns.
• Establish and govern architectural standards, API conventions, security patterns and observability requirements.
• Lead procurement evaluations and multi-cloud strategies balancing central services and local requirements.
• Architect enterprise security and governance with multi-stage security flows and guardrail architectures.
• Engage stakeholders and evangelize patterns across executive leadership and cloud partners.

Skills

Architectural credibility

LLM architecture

ADRs

Kubernetes (enterprise)

Multi-cloud (GCP & AWS)

OpenAI-compatible interfaces

API/design patterns

Education

Bachelor's degree or 4+ years experience

Master’s degree (preferred)

Tools

LangGraph

Google ADK

Job description

Verizon is seeking a Principal Architect for its Enterprise AI Platform to provide technical leadership across a 5-layer architecture serving global business units. You will drive architectural coherence, ADRs, ARB submissions, and rigorous build-vs-buy analyses with multi-year TCO models.

This role requires deep LLM expertise, enterprise-scale Kubernetes, and cross-functional collaboration with executives and engineering teams to shape the future of AI platforms.