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Verizon Communications

Runs wireless and fiber networks across the US

Senior Agentic AI Engineer

AI Application EngineeringPosted on Nov 11
Full-time$101k - $194k /yr

About the Job

Requirements

  • A bachelor's degree or four or more years of work experience is required.
  • Four or more years of relevant experience is required, demonstrated through work and/or military experience or specialized training.
  • Four or more years of relevant work experience, including two or more years focused on Generative AI, large language models, and autonomous agent systems, is required.
  • Four or more years of experience developing and implementing analytical or AI solutions to complex business problems is required.
  • Hands-on proficiency with multi-agent orchestration frameworks such as LangChain, LangGraph, Google Agent Development Kit, LlamaIndex, or AutoGen is required.
  • Experience designing agent-to-agent communication protocols, task delegation hierarchies, and the Model Context Protocol for enterprise tool integration is required.
  • Experience with agent memory and state management, including short-term context, long-term storage, context-window optimization, and stateful workflow execution, is required.
  • Knowledge of retrieval-augmented generation, ONNX-based embeddings, vector databases such as Pinecone, Weaviate, or pgvector, and semantic search is required.
  • Knowledge of cloud-scale data engineering, BigQuery pipelines, and Google Cloud Platform services such as Cloud Run and Vertex AI, or Amazon Bedrock or an Azure equivalent, is required.
  • Experience with Python and SQL for statistical modeling, prompt engineering, token management, and large-scale data extraction is required.

Responsibilities

  • Architect and deploy scalable multi-agent AI systems, including agent workflows, agent-to-agent communication protocols, and task-delegation hierarchies for cooperative AI agents.
  • Integrate large language models with enterprise systems through APIs, function calling, and the Model Context Protocol so agents can reason, plan, use tools, and act autonomously.
  • Build and operate enterprise Agent Factory pipelines that support autonomous, continuously executing intelligent workflows.
  • Design and implement retrieval-augmented generation systems with ONNX-based embeddings and vector databases to produce context-aware, personalized outputs at scale.
  • Manage agent memory and state architecture, implementing short-term, medium-term, and long-term memory using tools such as LangGraph for reliable multi-step task execution.
  • Own the agent and model lifecycle, including feature engineering, training, production deployment on Cloud Run or Vertex AI, and continuous monitoring with observability tooling.
  • Establish security guardrails, permission boundaries, short-lived agent identity tokens, and safety constraints for production agentic systems.
  • Develop and maintain propensity models, classification systems, and forecasting solutions that inform downstream agent decisions.
  • Translate complex agentic AI outputs into operational strategies and present findings to senior leadership and cross-functional business partners.
  • Perform advanced AI-augmented analytics and generative AI model validation to assess accuracy, reliability, and business performance.

Desired Qualifications

  • A master's degree in a quantitative discipline such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Operations Research.
  • Familiarity with machine-learning and large-language-model monitoring and observability tools such as OpenTelemetry, Arize Phoenix, or Galileo to track model drift, accuracy degradation, and agent-output quality.
  • Experience with generative AI-augmented analytics, AI testing frameworks, model-validation pipelines, and LLMOps tooling including observability and token management.
  • Experience with AI governance, security, compliance, and financial return-on-investment modeling for AI agent deployments.
  • Domain expertise in customer analytics, churn prediction, customer lifetime-value modeling, or related commercial analytics in consumer, telecommunications, financial services, or technology industries.
  • Experience educating and communicating AI findings to colleagues and executive stakeholders, including presenting AI strategy and business impact.
  • Curiosity, an investigative mindset, and flexibility to adapt to new challenges while maintaining focus on team deliverables.

About the Company

Verizon Communications

Runs wireless and fiber networks across the US

Verizon runs one of the largest wireless and fiber networks in the United States, selling mobile and home internet service to consumers, businesses and government agencies. Its consumer arm sells phone plans along with Fios and Frontier fiber internet and 5G home internet, which beams broadband to homes over its cellular network. Verizon Business sells mobile, networking and security services to companies of every size, including nearly all of the Fortune 500. Most revenue comes from monthly service plans, with more from device sales and installment payments. Verizon was incorporated in 1983 as Bell Atlantic, took the Verizon name in 2000, and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York, NY
Founded
1983

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