Principal AI Engineer, Forward-Deployed (Hybrid)

Verizon; Irving (TX); Hybrid; USD 121,000 - 231,000; Full time

Job summary

Verizon is hiring a Principal Forward Deployed AI Engineer to embed with frontline business units and own production-grade AI architectures. You will craft multi-agent orchestration, enterprise RAG engines, and scalable back-end integrations while guiding governance and tooling strategy across the company.

You will deploy and operate workloads on Domino, Airflow, Kubernetes, and cloud platforms, balancing performance, cost, and reliability with a product mindset and executive-facing

Qualifications

• Bachelor's degree or 4+ years of work experience in a technical field.
• 6+ years of relevant experience demonstrated across projects or military training.
• Hands-on with frontier LLMs and agentic developer frameworks to build scalable solutions.
• Experience shipping production software and deploying LLM applications into production.

Responsibilities

• Define full-stack architecture for embedded AI initiatives with multi-agent orchestration.
• Architect workflows using LangGraph, Temporal, or state machines with governance rules.
• Design production RAG infrastructure with hybrid search and semantic caching.
• Deploy production agent services to Domino, Airflow, Kubernetes, and cloud runtimes.
• Craft offline/online evaluation frameworks to measure model drift and performance.
• Generalize deployments into reusable SDKs and document architectures for IP.
• Embed with BU leadership to map processes and isolate high-leverage interventions.
• Act as technical authority, translating business needs into architectures for executives.

Skills

Python

TypeScript

LLMs

Agentic workflows

Education

Bachelor's degree in Computer Science

Tools

LangGraph

Temporal

Kubernetes

Job description

Verizon is hiring a Principal Forward Deployed AI Engineer to embed with frontline business units and own production-grade AI architectures. You will craft multi-agent orchestration, enterprise RAG engines, and scalable back-end integrations while guiding governance and tooling strategy across the company.

You will deploy and operate workloads on Domino, Airflow, Kubernetes, and cloud platforms, balancing performance, cost, and reliability with a product mindset and executive-facing