Principal Engineer- AI Platform Architect

Verizon•Irving, TX

1d•Hybrid

About The Position

As the Principal Architect for Verizon’s Enterprise AI Platform, you will provide technical leadership for a comprehensive 5-layer architecture serving all global business units. Your primary mandate is to ensure architectural coherence across the ecosystem, aligning Gateway routing with the Registry’s RBAC models, integrating the ADLC pipeline with established guardrail frameworks, and providing end-to-end token visibility for FinOps. In this capacity, you will author Architecture Decision Records (ADRs), spearhead Architecture Review Board (ARB) submissions, and conduct rigorous build-vs-buy analyses supported by multi-year Total Cost of Ownership (TCO) models. This principal-level individual contributor role requires the ability to exert technical influence and drive consensus across the organization through design excellence and strategic vision. Direct the 5-layer architecture stack — Encompassing Model Foundation, Agent Factory, Agent Runtime, Experience, and Control Plane layers. Responsibilities include defining formal layer boundaries, interface contracts, and interaction patterns to ensure platform scalability. Establish and govern architectural standards — Defining API conventions, enterprise security patterns, and observability requirements. Lead component reviews and provide consultative oversight for Business Unit agent architectures to ensure platform alignment. Lead technical strategy and procurement evaluations — Executing complex build-vs-buy analyses for platform components and develop comprehensive 3-year TCO models. Formulate multi-cloud strategies balancing central platform services with decentralized requirements. Architect enterprise security and governance frameworks — Designing multi-stage security flows encompassing identity, authentication, execution safety, and audit. Engineer Responsible AI (RAI) guardrail architectures and ensure compliance with emerging international regulations. Stakeholder engagement and pattern evangelization — Collaborating with executive leadership and external cloud partners on capacity planning and integration. Contribute high-impact reference architectures to the enterprise library to drive architectural maturity.

Requirements

Principal-level architect with a demonstrated focus on technical interface contracts and Total Cost of Ownership (TCO) modeling.
Proven history of designing scalable distributed platforms and establishing architectural credibility with both executive leadership and engineering teams through rigorous Architecture Decision Records (ADRs).
Deep technical proficiency in Large Language Model (LLM) architecture—including attention mechanisms, KV-cache, context windows, and token economics—is required, alongside the ability to substantiate build-vs-buy recommendations with robust, 3-year financial models.
Agility to navigate rapidly evolving AI technologies and the ability to drive strategic consensus and influence technical direction across the organization.
Bachelor's degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Experience in software or platform architecture, with designing AI/ML systems.
Experience as a system-level architect with proven ADRs and reference architectures.
Experience with agentic development and design patterns. (LangGraph and Google ADK)
Experience with distributed systems: service mesh, API gateways, event-driven patterns, multi-tenancy, and data isolation.
Experience with Kubernetes at enterprise scale.
Experience with LLM architecture — transformers, attention, KV-cache, context windows, token economics, and routing patterns.
Experience in multi-cloud environments (GCP and AWS).
Experience with API platform design: OpenAI-compatible interfaces, SDK design, developer experience.
Experience presenting architecture recommendations to VP/SVP-level leadership.

Nice To Haves

A Master’s degree in Computer Science, Engineering, or an MBA.
Experience architecting agentic AI systems — agent runtimes, multi-agent orchestration, memory systems.
Experience with security architecture: zero-trust (SPIFFE/SPIRE), mTLS, OPA, Vault, and regulated environments (CPNI, PCI-DSS).
Experience with MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocol design.
Experience designing RAG architectures (vector databases, hybrid search, re-ranking).
Experience with MLOps/LLMOps at scale (model registry, RLHF/RLAIF).
Experience with FinOps at scale — unit economics for AI workloads.
Telecom or regulated enterprise architecture background.
Experience architecting OpenTelemetry-based observability platforms.
Published architecture writing or open-source AI/ML contributions.
Certifications: AWS Solutions Architect Professional, GCP Professional Cloud Architect.

Responsibilities

Direct the 5-layer architecture stack — Encompassing Model Foundation, Agent Factory, Agent Runtime, Experience, and Control Plane layers. Responsibilities include defining formal layer boundaries, interface contracts, and interaction patterns to ensure platform scalability.
Establish and govern architectural standards — Defining API conventions, enterprise security patterns, and observability requirements. Lead component reviews and provide consultative oversight for Business Unit agent architectures to ensure platform alignment.
Lead technical strategy and procurement evaluations — Executing complex build-vs-buy analyses for platform components and develop comprehensive 3-year TCO models. Formulate multi-cloud strategies balancing central platform services with decentralized requirements.
Architect enterprise security and governance frameworks — Designing multi-stage security flows encompassing identity, authentication, execution safety, and audit. Engineer Responsible AI (RAI) guardrail architectures and ensure compliance with emerging international regulations.
Stakeholder engagement and pattern evangelization — Collaborating with executive leadership and external cloud partners on capacity planning and integration. Contribute high-impact reference architectures to the enterprise library to drive architectural maturity.