Principal AI Engineer

Verizon•Alpharetta, GA

4d•$120,500 - $231,000•Hybrid

About The Position

You will be building, optimizing, and deploying state-of-the-art agentic AI/ML models and systems within the Verizon Consumer Group (VCG) AI team. Applying hands-on technical expertise, you will be implementing next-generation customer success, sales, and digital agent solutions that directly impact how millions of customers interact with Verizon. Working as part of a high-performing squad, you will turn architectural designs into production-grade code while ensuring reliability, performance, and scale.

Requirements

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.
One or more years of hands-on experience building, tuning, or integrating AI/ML models and LLM applications.
Experience within Agile software development methodologies.

Nice To Haves

A degree in Computer Science, Engineering or related field.
Experience developing end-to-end AI agents and RAG architectures using orchestration frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK).
Hands-on experience with cloud-native technologies, API design, and Google Cloud Platform (GCP).
Familiarity with enterprise AI integrations and performance management platforms (e.g., Verint).
Strong prioritization skills with a track record of managing multiple projects in fast-paced environments.

Responsibilities

Developing, testing, and scaling agentic AI/ML solutions, specialized workflows, and LLM-powered systems for Verizon Consumer Group platforms.
Integrating AI agent frameworks with existing customer success, digital, and retail channel technologies.
Collaborating with product managers and engineering teams to implement and iterate on production-grade technical roadmaps.
Participating in engineering code reviews, technical design sessions, and red-teaming exercises to ensure safe and reliable model behaviors.
Optimizing model inference pipelines, API endpoints, and data integration layers to meet high-performance consumer demands.
Assisting in technical research and rapid prototyping to quickly evaluate and implement emerging open-source and proprietary AI frameworks.
Contributing to the documentation of technical specifications and creating materials to showcase pilot performance results.