AI Engineer - GenAI and Agentic AI

Cellco Partnership; Irving (TX); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Verizon is seeking an AI Engineer for its Marketing Technology Group to design, build and deploy LLM-powered agents and multi-agent workflows. You’ll ground agents in enterprise data, develop RAG pipelines, and integrate tools and APIs to automate business tasks with guidance from senior engineers.

You will measure quality, latency, and cost, monitor models in production, and collaborate with global cross-functional teams to turn complex requirements into reliable agent solutions in a fast-paced

Qualifications

• Bachelor’s degree or 4+ years of work experience.
• 4+ years of relevant work experience.
• 2+ years of hands-on experience in machine learning, data science or AI engineering, including Generative AI or LLM-based projects.
• 2+ years of experience with Python and SQL.
• Experience building applications with LLMs, including prompt engineering, RAG and tool or function calling.
• Experience with cloud computing environments (e.g., GCP, AWS or Azure).
• Experience in quantitative skills in math, statistics or related fields.

Responsibilities

• Build AI agents and multi-agent workflows that automate business tasks with guidance from senior team members.
• Develop GenAI capabilities including RAG pipelines and tool/API integrations.
• Evaluate agent accuracy, response quality and latency and implement guardrails and monitoring for production reliability.
• Deploy agents and models in real-time and batch environments and monitor performance and costs.
• Collaborate with business stakeholders and senior engineers to translate requirements into working agent solutions.
• Research and test new LLMs, agent frameworks and GenAI methods and share viable ideas with the team.

Skills

AI engineering

Python

SQL

Machine learning

GenAI

Data science

Education

Bachelor's degree or 4+ years experience

Tools

LangChain

LangGraph

CrewAI

AutoGen

Google ADK

MCP

pgvector

Pinecone

Elasticsearch

Job description

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.

Why build AI at Verizon?

Most early-career AI roles keep builders stuck on isolated prototypes, internal chatbots, or low-stakes demos that never make it past a proof-of-concept. In Verizon's Marketing Technology Group, you'll build production-grade agentic AI systems that directly power how a $130B+ enterprise sells, serves, and operates. Working alongside senior AI engineers and product owners, you'll design and deploy multi-agent workflows, RAG pipelines, and tool-integrated LLMs using modern stacks (LangGraph, Google ADK, MCP) that elevate sales productivity and service operations for thousands of employees and millions of customers. Backed by Verizon's multi-year investment to industrialize AI-and deep partnerships with hyperscalers like Google Cloud and AWS-this is your opportunity to master production guardrails, latency optimization, and real-world agent orchestration while accelerating your growth as an AI engineer.

What you'll be doing ...

• Build AI Agents: Design, build and deploy LLM-powered agents and multi-agent workflows that automate business tasks, with guidance from senior team members.
• Develop GenAI Capabilities: Build retrieval-augmented generation (RAG) pipelines, tool and API integrations, and prompts that ground agents in enterprise data.
• Evaluate & Improve Quality: Measure agent accuracy, response quality and latency, and apply evaluation methods, guardrails and monitoring so agents stay reliable in production.
• Deploy & Monitor in Production: Help deploy agents and models in real-time and batch environments, and track their performance, cost and drift.
• Partner with the Business: Work with business stakeholders and senior engineers to understand requirements and turn them into working agent solutions.
• Learn & Innovate: Research and test new LLMs, agent frameworks and GenAI methods, and bring promising ideas to the team.

What we're looking for...

You bring strong analytical instincts and a passion for solving business problems with Generative AI. You learn quickly, take ownership of your assigned work, communicate your results clearly, and collaborate well with global, cross-functional engineering teams in a fast-paced environment.

You'll need to have...

• Bachelor's degree or four or more years of work experience
• Four or more years of relevant work experience
• Two or more years of hands-on experience in machine learning, data science or AI engineering, including Generative AI or LLM-based projects.
• Two or more years of experience with Python and SQL.
• Experience building applications with LLMs, including prompt engineering, RAG and tool or function calling.
• Experience with cloud computing environments (e.g., GCP, AWS or Azure).
• Experience in quantitative skills in math, statistics or related fields.

Even better if you also have...

• Master's degree or Ph.D. in a quantitative field (Computer Science, Data Science, Statistics, Math, Engineering or Economics).
• Experience building and deploying AI agents to production, including evaluation, guardrails and observability.
• Experience with vector databases (e.g., pgvector, Pinecone or Elasticsearch) and embedding models.
• Experience with at least one agent framework, such as LangChain, LangGraph, CrewAI, AutoGen or Google ADK.
• Familiarity with the Model Context Protocol (MCP) or multi-agent orchestration.
• Experience with traditional machine learning, deep learning and NLP.
• Ability to explain technical concepts and results clearly to non-technical audiences.

Where you'll be working

In this hybrid role, you'll have a defined work location that includes working from home