Distinguished Engineer AI Science

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We are seeking a visionary Distinguished Engineer, AI Science to lead the technical strategy, research, and development of our next-generation AI architecture focused on Customer Base Management (CVM). As a Distinguished Engineer, you will be the foremost technical authority in the organization, driving the evolution from traditional machine learning to advanced Agentic, Predictive, and Prescriptive AI systems.

You will design autonomous, AI-driven engines that maximize the lifetime value of our customer base, architecting systems that not only predict customer behavior but prescribe dynamic, real-time interventions and execute them autonomously via multi-agent frameworks.

Key Responsibilities

1. Visionary Technical Leadership & AI Strategy

• Serve as the chief technical architect and visionary for all AI science initiatives related to Base Management, Customer Lifetime Value (CLTV), churn mitigation, and cross-sell/upsell monetization.
• Define the multi-year roadmap for integrating Agentic AI (autonomous agents, LLM-driven decision engines) into our core base management platforms.
• Bridge the gap between foundational AI research and enterprise-scale commercial impact, advising C-level executives on AI investments and technology bets.

2. Advanced AI Modeling & Agentic Architecture

• Agentic AI: Architect multi-agent systems and LLM-backed autonomous pipelines capable of executing complex customer lifecycle interventions without human-in-the-loop dependencies.
• Predictive AI: Oversee the development of state-of-the-art predictive models (deep learning, sequence modeling, probabilistic models) for extreme-accuracy forecasting of churn, propensity, and customer lifecycle events.
• Prescriptive AI: Design large-scale optimization and reinforcement learning (RL) engines that determine the "Next Best Action" (NBA), Next Best Offer (NBO), and dynamic pricing strategies in real-time.
• Pioneer the use of Generative AI for hyper-personalized base communication, ensuring safety, compliance, and brand alignment within agentic workflows.

3. Base Management Innovation

• Transform traditional Customer Value Management (CVM) into a continuous, real-time, AI-native discipline.
• Develop scalable algorithms for causal inference and uplift modeling to ensure AI interventions generate true incremental value (A/B testing at scale).
• Collaborate closely with Product, Marketing, and Operations leaders to deploy AI solutions that fundamentally alter the economics of customer retention and growth.

4. Mentorship & Eminence

• Act as a technical mentor and sponsor for Principal Scientists, Senior Machine Learning Engineers, and Data Scientists across the organization.
• Drive a culture of engineering and scientific excellence, establishing rigorous standards for model validation, MLOps, AI safety, and ethical AI.
• Represent the company in the broader AI community through conference presentations, whitepapers, open-source contributions, and patent filings.

Required Qualifications

• Education: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Operations Research, or a closely related highly quantitative field.
• Experience: 12+ years of applied R&D experience in AI/ML, with at least 5+ years in a senior technical leadership role (Principal Engineer, Chief Scientist, or equivalent).
• Domain Expertise: Deep understanding of Base Management, Customer Value Management (CVM), algorithmic marketing, and lifecycle optimization.
• Technical Mastery:Expertise in Predictive AI (Deep Learning, NLP, Time-Series forecasting, Graph Neural Networks).Expertise in Prescriptive AI (Reinforcement Learning, Contextual Bandits, Mathematical Optimization, Operations Research).Cutting-edge knowledge of Agentic AI (LLMs, LangChain/LlamaIndex, multi-agent frameworks like AutoGen, tool-augmented language models).
• Engineering Prowess: Proven track record of architecting and deploying ultra-low latency, high-throughput AI systems into production. Fluency in Python, C++, or similar, and deep familiarity with scalable cloud architectures (AWS/GCP/Azure) and MLOps platforms.
• Impact: Demonstrable history of driving hundreds of millions of dollars in enterprise value through the application of AI to customer bases.

Preferred Qualifications

• Recognized industry eminence (e.g., highly cited publications at NeurIPS, ICML, KDD, ACL, or strong portfolio of impactful patents).
• Experience transitioning legacy rule-based business logic systems into fully autonomous RL or Agentic AI decision engines.
• Deep expertise in Causal ML and Double Machine Learning for uplift modeling.

Where you’ll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.