R-1101008 Senior AI Engineer

Verizon•Basking Ridge, NJ

1d•Hybrid

About The Position

As a Senior AI Engineer on Verizon’s propensity modeling team, you will support the company’s transition to a modern, agile pod model. You will work on customer lifecycle touchpoints and high-impact trigger events, applying advanced machine learning to enable micro-segmentation and hyper-personalization. The work supports marketers, improves customer journeys, and helps reduce churn across critical customer segments. You will lead the development and optimization of agentic AI, LLM, and machine learning solutions; manage complex propensity models from development through production; and own model optimization and performance. You will also provide technical guidance to junior data scientists and communicate model insights and recommendations to senior leaders and business partners.

Requirements

Bachelor's degree or four or more years of work experience.
Four or more years of relevant experience, demonstrated through work experience and/or military experience.
Experience working on high-priority or high-visibility technical initiatives within a corporate setting.
Knowledge of LLM agent architecture, including Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation (RAG), MCP, and A2A protocols.
Experience using Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
Strong expertise in machine learning/deep learning algorithms, including Transformers, transfer learning, and NLP, and experience using PyTorch and scikit-learn.

Nice To Haves

Master’s degree.
Experience with RAG, ONNX-based embeddings, vector databases, and semantic search.
Knowledge of cloud-scale data engineering, including BigQuery pipelines and GCP services such as Cloud Run and Vertex AI.
Experience with cloud platforms such as GCP, AWS, or Azure, and production MLOps tools for tracking and maintaining model workflows.
Experience building, evaluating, and deploying end-to-end propensity models, such as likelihood-to-buy, churn prediction, lead scoring, and cross-sell models, using machine learning algorithms.

Responsibilities

Lead the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions.
Build, train, and deploy complex, high-priority propensity models to predict customer behavior, churn risk, and lifecycle triggers.
Independently manage end-to-end model development pipelines, from advanced feature engineering through production deployment and monitoring.
Serve as a subject matter expert in agentic development, machine learning, and predictive modeling, providing technical guidance and mentorship to junior data scientists.
Own the lifecycle of models deployed in high-impact areas, ensuring continuous optimization, accuracy, and measurable business performance.
Present model insights, performance metrics, and strategic recommendations to senior leadership and cross-functional business partners.

Benefits

Medical, dental, and vision benefits.
Short- and long-term disability insurance.
Basic and supplemental life insurance and AD&D insurance.
Identity theft protection, pet insurance, and group home and auto insurance.
Matched 401(k) savings plan.
Up to 8 company-paid holidays per year and up to 6 personal days per year.
Paid parental leave.
Adoption assistance.
Tuition assistance.
New hires receive up to 15 vacation days per year, with vacation increasing with additional service.
Potential incentive-based compensation and premium pay, depending on the role.