Senior Agentic AI Engineer

About the role

Join Verizon, a leader in powering and empowering how people live, work, and play by connecting them to what brings them joy. As a Senior Agentic AI Engineer, you will be at the forefront of Verizon's transformation towards centralized intelligence and enterprise-grade AI agents that drive action.

Responsibilities

• Architect and deploy scalable multi-agent AI systems—designing agent workflows, communication protocols (A2A), and task delegation hierarchies for fleets of cooperative AI agents.
• Integrate LLMs with enterprise systems via APIs, function calling, and the Model Context Protocol (MCP) to enable agents that can reason, plan, use tools, and act autonomously.
• Build and operate enterprise Agent Factory pipelines—moving from reactive, episodic analytics to autonomous, continuously executing intelligent workflows.
• Design and implement retrieval-augmented generation (RAG) systems with ONNX-based embeddings and vector databases to power context-aware, hyper-personalized outputs at scale.
• Manage agent memory and state architecture—implementing short-term, medium-term, and long-term memory using tools like LangGraph for reliable multi-step task execution.
• Owning the full agent and model lifecycle: feature engineering, training, production deployment (Cloud Run, 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 feed downstream agent decision-making.
• Translate complex agentic AI outputs into clear operational strategies and present findings to senior leadership and cross-functional business partners.
• Perform advanced AI-augmented analytics and generative AI model validation to ensure accuracy, reliability, and measurable business performance.

Requirements

• Bachelor's degree or four or more years of work experience.
• Four or more years of relevant experience, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Four or more years of relevant work experience, with two or more years focused specifically on Generative AI, LLMs, and autonomous agent systems.
• Four or more years of experience developing and implementing analytical or AI solutions to complex business problems.
• Hands-on proficiency with multi-agent orchestration frameworks: LangChain, LangGraph, Google Agent Development Kit (ADK), LlamaIndex, or AutoGen.
• Experience designing agent-to-agent (A2A) communication protocols, task delegation hierarchies, and the Model Context Protocol (MCP) for enterprise tool integration.
• Demonstrated knowledge of retrieval-augmented generation (RAG), ONNX-based embeddings, vector databases (Pinecone, Weaviate, pgvector), and semantic search.
• Demonstrated knowledge of cloud-scale data engineering: BigQuery pipelines and GCP (Cloud Run, Vertex AI, Amazon Bedrock, or Azure equivalent).
• Experience with Python and SQL for statistical modeling, prompt engineering, token management, and large-scale data extraction.

Qualifications

• A Master's degree in a quantitative discipline such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Operations Research.
• Familiarity with ML/LLM monitoring and observability tooling (e.g., OpenTelemetry, Arize Phoenix, Galileo) for tracking model drift, accuracy degradation, and agent output quality over time.
• 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 ROI modeling for AI agent deployments.
• Domain expertise in customer, churn prediction, customer lifetime value (CLV) modeling, or related commercial analytics in Consumer, Telecommunications, Financial Services, or Technology industries.
• A passion for educating and communicating AI findings with integrity to all levels—from reviewing raw outputs with colleagues to presenting AI strategy and business impact to executive stakeholders.

Skills

• Strong foundation in data science and machine learning.
• Strategic vision to evaluate when an autonomous agent is the right solution.
• Communication skills to explain complex, probabilistic AI behaviors clearly to executive, security, and business stakeholders.

Benefits and Compensation

Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance. We also offer a 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 and tuition assistance, plus other incentives, we’ve got you covered with our award-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances. The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours. The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $101,000.00 - $194,000.00.