Senior Agentic AI Engineer

Verizon; New Jersey; On-site; USD 140,000 - 230,000; Full time

Job summary

Verizon is seeking a Senior Agentic AI Engineer to lead the architecture and deployment of multi-agent systems that reason, plan, and act across complex business domains. You will advance enterprise-grade AI agents, integrate LLMs via APIs, and implement retrieval-augmented generation and memory architectures.

You've moved beyond model building into end-to-end agentic systems, with data science and ML foundations, and can articulate autonomous agent value to senior leaders and cross-functional

Responsibilities

• Architecting and deploying scalable multi‑agent AI systems—designing agent workflows, communication protocols (A2A), and task delegation hierarchies for fleets of cooperative AI agents.
• Integrating 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.
• Building and operating enterprise Agent Factory pipelines—moving from reactive, episodic analytics to autonomous, continuously executing intelligent workflows.
• Designing and implementing retrieval‑augmented generation (RAG) systems with ONNX‑based embeddings and vector databases to power context‑aware, hyper‑personalized outputs at scale.
• Managing 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.
• Establishing security guardrails, permission boundaries, short‑lived agent identity tokens, and safety constraints for production agentic systems.
• Developing and maintaining propensity models, classification systems, and forecasting solutions that feed downstream agent decision‑making.
• Translating complex agentic AI outputs into clear operational strategies and presenting findings to senior leadership and cross‑functional business partners.
• Performing advanced AI‑augmented analytics and generative AI model validation to ensure accuracy, reliability, and measurable business performance.

Job description

Apply prior to the end date: November 28, 2026

When you join Verizon

You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What you'll be doing…

As a Senior Agentic AI Engineer within our team, you will be at the forefront of Verizon's transformation toward centralized intelligence and enterprise‑grade AI agents that drive action. Our team manages a broad portfolio of business processes underpinned by analytics, and you will lead the evolution from reactive reporting to autonomous, intelligent execution. You will architect and deploy multi-agent systems capable of reasoning, planning, and collaborating across complex business domains—closing the loop between AI investment and measurable business outcomes.

Responsibilities include:

• Architecting and deploying scalable multi‑agent AI systems—designing agent workflows, communication protocols (A2A), and task delegation hierarchies for fleets of cooperative AI agents.

• Integrating 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.

• Building and operating enterprise Agent Factory pipelines—moving from reactive, episodic analytics to autonomous, continuously executing intelligent workflows.

• Designing and implementing retrieval‑augmented generation (RAG) systems with ONNX‑based embeddings and vector databases to power context‑aware, hyper‑personalized outputs at scale.

• Managing 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.

• Establishing security guardrails, permission boundaries, short‑life​d agent identity tokens, and safety constraints for production agentic systems.

• Developing and maintaining propensity models, classification systems, and forecasting solutions that feed downstream agent decision‑making.

• Translating complex agentic AI outputs into clear operational strategies and presenting findings to senior leadership and cross‑functional business partners.

• Performing advanced AI‑augmented analytics and generative AI model validation to ensure accuracy, reliability, and measurable business performance.

Translating complex agentic AI outputs into clear operational strategies and presenting findings to senior leadership and cross‑functional partners is also part of the role. Performing advanced AI‑augmented analytics and generative AI model validation to ensure accuracy, reliability, and measurable business performance.

What we're looking for…

You are a senior AI engineer who has moved beyond building models into building agents—systems that reason, plan, and act. You have a strong foundation in data science and machine learning, and you've extended that into LLM orchestration, multi‑agent architecture, and production agentic systems. You have the strategic vision to evaluate when an autonomous agent is the right solution, and the communication skills to explain complex, probabil