Principal AI Engineer

Verizon

Principal AI Engineer leading propensity model development and machine learning initiatives at Verizon. Collaborating with marketing teams to optimize customer engagement and retention strategies.

Posted 7/31/2026full-timeNew Jersey, Texas • 🇺🇸 United StatesLead💰 $120,500 - $231,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing, deploying, and optimizing complex machine learning models, with a focus on propensity modeling and customer behavior prediction. Proficient in managing end-to-end model development pipelines and collaborating with marketing stakeholders to enhance customer journeys and reduce churn.

Highest-signal resume keywords

Machine Learning Model DevelopmentPropensity ModelingCloud-Scale Data EngineeringPython ProgrammingAdvanced Feature Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPropensity ModelsStatistical ModelingData ExtractionFeature EngineeringModel DeploymentModel MonitoringAdvanced Statistical AnalysisRAG (Retrieval-Augmented Generation)Vector Databases

Soft Skills

CollaborationIndependenceProblem SolvingCommunication

Tools & Technologies

Google ADKLangChainGCP (Cloud Run, Vertex AI)BigQueryONNX

Industry Keywords

Customer LifecycleMicrosegmentationHyper-PersonalizationChurn RiskData Engineering

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Serve as a lead within our team of propensity modelers, driving the technical execution of Verizon’s transition to a modern, agile pod model
Operate with a high degree of independence, owning our most complex propensity models and supporting Verizon's highest-priority, highest-visibility base management pods
Work directly at the critical touchpoints of the customer lifecycle and high-impact trigger events
Provide the advanced machine learning support needed to unlock deep microsegmentation and hyper-personalization
Empower marketers, optimize customer journeys, and drive down churn across our most critical customer segments
Build, train, and deploy our most complex and high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers
Manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring
Collaborate closely with high-visibility base management pods and senior marketing stakeholders

Requirements

What you’ll need

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
Four or more years of experience independently developing, deploying, and optimizing complex machine learning or propensity models in a production environment
Experience working on high-priority or high-visibility technical initiatives within a corporate setting
Knowledge of LLM agent architecture: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG , MCP, A2A protocols
Experience with retrieval-augmented generation (RAG), ONNX-based embeddings, vector databases and semantic search
Knowledge of cloud-scale data engineering: BigQuery pipelines, GCP (Cloud Run, Vertex AI)
Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction

Benefits

Comp & perks

medical, dental, vision
short and long term disability
basic life insurance
supplemental life insurance
AD&D insurance
identity theft protection
pet insurance
group home & auto insurance
matched 401(k) savings plan
up to 8 company paid holidays per year
up to 6 personal days per year
paid parental leave
adoption assistance
tuition assistance
other incentives
up to 15 days of vacation per year