Senior AI Engineer

Verizon•Basking Ridge, NJ

1d•Hybrid

About The Position

As a Senior AI Engineer within Verizon's team of propensity modelers, you will be responsible for the technical execution of Verizon's transition to a modern, agile pod model. You will work directly at the critical touchpoints of the customer lifecycle and high-impact trigger events, providing the advanced machine learning support needed to unlock deep micro segmentation and hyper-personalization. Your work will directly empower marketers, optimize customer journeys, and drive down churn across our most critical customer segments.

Requirements

Bachelor's degree or four or more years of work experience.
Four or more years of relevant experience required, 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: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG , MCP, A2A protocols.
Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
Strong expertise in machine learning/deep learning algorithms, including Transformer, transfer learning, NLP, and expertise in using Pytorch and scikit-learning packages.

Nice To Haves

Master’s degree.
Experience with retrieval-augmented generation (RAG), ONNX-based embeddings, vector databases and semantic search
Knowledge of cloud-scale data engineering: Big Query pipelines, GCP (Cloud Run, Vertex AI).
Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.
Experience building, evaluating, and deploying end-to-end propensity models (e.g., likelihood-to-buy, churn prediction, lead scoring, cross-sell) 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 our most complex and high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers.
Operate independently to manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
Serve as a subject matter expert on 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 complex model insights, performance metrics, and strategic recommendations clearly to senior leadership and cross-functional business partners.