Associate Director, AI Engineering - Live Operations

Verizon•Alpharetta, GA

1d•$126,000 - $242,000•Hybrid

About The Position

As the Associate Director of AI/ML Engineering - Live Operations, you will use your deep technical expertise in data science and real-time AI systems to lead a high-performing team focused on the production lifecycle, health, and optimization of our deployed models. You will play a pivotal role in ensuring our commercial AI applications remain highly accurate, safe, and operationally efficient once they interact with real-world users. At Verizon, we are on a multi-year journey to industrialize our data science and AI capabilities. Very simply, this means that AI will fuel decisions and business processes across the company. At over one hundred thirty billion dollars in annual revenue, this is a pioneering opportunity to design, scale, and maintain production AI in the telecommunications industry. With our leadership in bringing 5G network nationwide, the opportunity for AI will only grow exponentially as we transition from enabling billions of automated, real-time predictions to trillions.

Requirements

Bachelor’s degree or four or more years of work experience.
Eight or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
You can visualize the big picture strategy but can also break it down into the operational components required to keep complex systems running flawlessly.
You understand that once an AI model interacts with live users, the real work begins.
You have credibility with engineering and business teams alike because you speak the language of deep data science but can translate technical complexity into clear business value.
You are also an inspiring leader who thrives in a fast-paced environment and brings out the best in your team.

Nice To Haves

Master’s degree in statistics, mathematics, analytics, engineering, computer science, or another technical discipline.
Direct experience managing teams of data scientists or research-oriented talent in a production, operations, or LiveOps capacity.
In-depth working experience with deep learning frameworks (such as PyTorch), Generative AI (such as Large Language Models, Multimodal LLMs, and Alignment), and distributed computing systems.
Experience building and maintaining automated model monitoring, evaluation, and CI/CD pipelines in a cloud or edge production environment.
High-level understanding of, and the ability to explain, both the software engineering code and the underlying mathematical algorithms.
Proficiency in developing real-time safety filters, system guardrails, and automated fallback systems for conversational or predictive AI.
Coding proficiency in Python, Java, or R, alongside experience with AWS, Hadoop, or other distributed compute platforms.

Responsibilities

Leading a talented, diverse team of AI scientists focusing on the continuous operations, health, and evolution of live production models.
Monitoring and observing real-world model performance to proactively detect model drift, track latency, and manage computational expenses, including token costs for large language models.
Designing and implementing continuous evaluation loops to systematically capture user feedback and ground-truth outcomes to assess model accuracy on a day-to-day basis.
Managing incident response protocols, rapid hotfixing, and automated safety guardrails to block inappropriate inputs or outputs before they reach the customer.
Establishing fallback architectures, such as routing users to human agents or traditional rule-based systems, to ensure a seamless experience if a model fails.
Automating continuous deployment (CI/CD) pipelines to pull new data, retrain models, test them against strict safety benchmarks, and deploy updates without user disruption.
Operating as a technical thought leader and trusted advisor to partner with broader data science teams, external vendors, and senior leadership.
Building an inclusive, highly engaged team culture that promotes autonomy, technical excellence, and rapid delivery of business outcomes.