Senior Agentic AI Engineer

When you join Verizon

You want more out of a career. A place to share your ideas freely even if theyre 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 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 youll be doing

As a Senior Agentic AI Engineer within our team you will be at the forefront of Verizons 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 domainsclosing the loop between AI investment and measurable business outcomes.

Responsibilities include:

• Architecting and deploying scalable multi-agent AI systemsdesigning 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 pipelinesmoving 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 architectureimplementing 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.

What were looking for

You are a senior AI engineer who has moved beyond building models into building agentssystems that reason plan and act. You have a strong foundation in data science and machine learning and youve 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 probabilistic AI behaviors clearly to executive security and business stakeholders.

Youll need to have:

• Bachelors degree or four or more years of work experience.
• Four or more years of relevant experience required 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.
• Experience with agent memory and state management: short-term context long-term storage context window optimization and stateful workflow execution.
• 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.

Even better if you have one or more of the following:

• A Masters 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 levelsfrom reviewing raw outputs with colleagues to presenting AI strategy and business impact to executive stakeholders.
• High curiosity an investigative mindset and the flexibility to adapt to new challenges while staying focused on the teams deliverables.
  

If Verizon and this role sound like a fit for you we encourage you to apply even if you dont meet every even better qualification listed above.

Where youll be working

In this hybrid role youll have a defined work location that includes working from home and a minimum of three days per week in the office which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status disability or other legally protected characteristics.

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 weve 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: $101000.00 - $194000.00.

Required Experience:

Senior IC