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Frontier Communications

Forward Deployed Engineer

AI Application EngineeringUpdated on Nov 14
Full-time$101k - $194k /yr

About the Job

Requirements

  • A bachelor's degree or four or more years of work experience.
  • Four or more years of relevant experience, demonstrated through work and/or military experience or specialized training.
  • Intermediate proficiency in Python or R, SQL, and a moderate history or portfolio of accomplished projects.
  • Intermediate proficiency in Alteryx or Knime.
  • Experience building or integrating agentic AI workflows, such as LLM-based agents, tool-use/function-calling pipelines, or frameworks such as LangChain, AutoGen, or Claude/GPT-based agents, to automate data ingestion, scenario generation, or report synthesis for capital planning and simulation workflows.

Responsibilities

  • Work with stakeholders to develop AI, agent-based modeling, and algorithmic modeling for network elements and processes supporting the three-year capital budget.
  • Plan and execute the design of a new capacity model and obtain general agreement from Network Capital Strategy and the business team.
  • Operate the model at multiple checkpoints during the year, create a hardened deployment and documentation, and plan future automation of the process.
  • Plan future model upgrades using alternative algorithms, AI science, or additional input features.
  • Leverage and pilot AI tools, including agentic workflows, LLM-assisted coding, and automated documentation and reporting, to accelerate model development, scenario testing, and stakeholder deliverables.
  • Adapt to and navigate roadblocks in the software development process, resolve issues independently, and escalate roadblocks when appropriate.
  • Present the nature of created systems occasionally to leaders and engineers.
  • Pursue patents when appropriate to protect invented Verizon intellectual property.

Desired Qualifications

  • A degree in business intelligence and analytics, data science, engineering, computer science, mathematics, or a similar field.
  • Experience in time-series analysis or forecasting.
  • Experience in engineering investigations, performance optimizations, or network capacity management.
  • Prior experience navigating engineering budget cycles, such as funding requests for cell-site builds in a regional role.
  • Experience gathering requirements and translating them into specific software practices.
  • Experience with data engineering.
  • Knowledge of cloud computing platforms such as Google Cloud Platform or Amazon Web Services.
  • Experience with high-performance containerized GPU environments.
  • A solid foundation in mathematical optimization, prescriptive modeling, and network capacity management.
  • Experience designing, architecting, and deploying full-stack web applications and APIs using frameworks such as FastAPI, custom GUIs such as Flet or Marimo, and high-performance BI dashboards to expose optimization models, streamline data ingestion, and accelerate scenario planning for non-technical leadership.

About the Company

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