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Verizon Data Services LLC

Principal Forward Deployed AI Engineer

Basking Ridge, NJ, United States
Irving, TX, United States
Charlotte, NC, United States
Temple Terrace, FL, United States

$120,500 to $231,000 USD / year

Apply on verizon.wd12.myworkdayjobs.com About employer

Applications open in a new tab.

Job details

Pay: $120,500 to $231,000 USD / year
Apply by: Dec 14, 2026
Work location: In this hybrid role, you'll 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
Posting language: English
Posted: Nov 13, 2026

Original 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.

What you’ll be doing...

As a Principal Forward Deployed AI Engineer within Verizon’s Transformation Command Center (TCC), you will embed directly into the frontline of Verizon’s core Business Units to solve our most critical, ambiguous, and high-stakes operational challenges. Operating with end-to-end technical ownership, you will architect, build, and deploy production-grade agentic systems, enterprise RAG engines, full-stack microservices, and decision systems into live operations.

In this role, you’ll embed with Network Capital Strategy (NCS) to lead the shift to agent-first capital modeling. You’ll apply AI, statistical, and advanced analytics methods to complex questions about where, when, and how to invest in the Verizon network, across a portfolio of models spanning demand forecasting, solution prioritization, and total cost of ownership. The goal is to size and prioritize multi-billion-dollar network investments so each capital dollar goes where it delivers the most value for our customers, with results the planning, engineering, and finance teams who fund and build the network can trust and trace.

You are a technical anchor: You pair deep systems craftsmanship and modeling rigor with a product mindset, cutting through operational ambiguity to design production architectures, implement custom orchestration layers (via LangGraph, Temporal, or custom state machines), and enforce context management strategies that scale into enterprise assets. Beyond shipping point solutions, you will run workloads reliably on Domino, Airflow, and Kubernetes, abstracting bespoke code into reusable SDKs, shared libraries, and architectural playbooks that scale company-wide.

Key Responsibilities include:

Applied Modeling & Research: Research and apply advances in statistics, machine learning, and AI to capital planning problems such as demand forecasting, solution prioritization, optimization, and impact measurement, and build the results into production models.
End-to-End Architectural Blueprinting: Define the full-stack architecture for embedded AI initiatives, including multi-agent orchestration, state machines, latency/cost budgets, security boundaries, and enterprise back-end integrations.
Agentic Orchestration Engineering, Workflow Automation and Governance: Architect stateful agent workflows complying with established agentic governance rules, using tools like LangGraph, Temporal, or event-driven state machines, establishing strict protocols for tool calling, execution sandboxing, and deterministic fallback logic.
Context & Retrieval Systems: Design production RAG infrastructure incorporating hybrid search, re-ranking algorithms, metadata filtering, and semantic caching, directly informing and scaling Verizon’s context architecture. Apply these systems to extract signal from unstructured engineering and project documents.
Runtime & Cloud Deployment: Deploy production agent services and scheduled workflows to target runtimes (e.g., Domino Data Lab, Apache Airflow, Kubernetes microservices, and serverless compute across AWS, GCP, or Azure).
Evaluation Harness Design: Architect offline and online evaluation frameworks (e.g., LLM-as-a-judge, synthetic test generation, backtesting against actuals, human-in-the-loop review queues, live A/B rollouts) to measure model drift, context hallucination rates, and task completion metrics, so AI-assisted capital recommendations stay explainable and traceable.
Platform Codification & IP Creation: Generalize custom domain deployments into reusable internal SDKs, API primitives, modular UI components, and standardized modeling procedures; mentor engineers across the organization and lead invention disclosures and patent filings.
Strategic Discovery & Scoping: Embed alongside BU leadership to map intricate operational processes, cut through organizational noise, and isolate the highest-leverage intervention points where applied AI delivers measurable uplift.
Executive Translation: Serve as the technical authority in the room with BU Vice Presidents and Managing Directors, demystifying algorithmic behaviors, failure modes, and performance trade-offs.

What we’re looking for...

You’ll need to have:

Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Six or more years building production software or models, including demonstrated experience deploying LLM applications, agentic workflows, or tool-calling pipelines.
Extensive hands-on experience using frontier LLMs (e.g., Anthropic Claude, OpenAI, Google Gemini) and agentic coding tools (e.g., Claude Code, Cursor, Copilot) to deliver solutions with measurable business outcomes.
A strong foundation in statistics and machine learning, applied to problems such as forecasting, prioritization, or optimization.
Proven track record designing offline and online evaluation harnesses, guardrail frameworks, and observability systems (e.g., latency, token costs, hallucination tracking, tracing).
Advanced proficiency in Python and SQL, plus working proficiency in TypeScript/Node.js for API integration and backend orchestration.
Proven experience designing APIs and deploying containerized services (Docker) and data workflows on platforms such as Apache Airflow, Kubernetes (EKS/GKE), and Domino Data Lab, across AWS, GCP, or Azure.
Demonstrated ability to independently scope ambiguous initiatives, translate business requirements into technical architectures, lead delivery end-to-end, and present designs to senior executives.

Even better if you have:

Bachelor's or Master’s degree in Computer Science, Machine Learning, Robotics, or a related technical field.
Experience building and scaling centralized context platforms or enterprise search engines similar to Verizon’s internal enterprise context layer platforms.
Deep expertise in retrieval and context architectures: designing production RAG pipelines, vector databases (e.g., pgvector, Milvus, Pinecone), hybrid search (dense + sparse/lexical), and dynamic context management.
Deep experience in time series forecasting, mathematical optimization, or causal inference.
Experience with model risk management, explainability, or validation of models used in high-stakes decisions.
Prior forward-deployed engineering, solutions architecture, or technical consulting experience in top-tier technology firms or hyperscalers.
A track record of turning one-off operational builds into enterprise-wide shared libraries, with associated technical publications or filed patents.
Domain knowledge in telecommunications, network capacity optimization, capital planning, or large-scale customer care operations.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.

Where you’ll be working

In this hybrid role, you'll 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, 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: $120,500.00 - $231,000.00.

Apply on verizon.wd12.myworkdayjobs.com About employer

More about this job

Skills

Microservices
Forecasting
Prioritization
IBM Domino
Apache Airflow
Kubernetes
Research
Statistics
Machine learning
Workflow
AWS
Google Cloud
Microsoft Azure
Leadership
Translation
Industrial software
Python
SQL
TypeScript
Node.js
Docker
Computer science
Robotics
Search engines
Risk management
Provide technical expertise
Customer service
Regulatory compliance

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Work requirements

Jobs in the United States