Senior AI Engineer

Verizon Verizon · Telecom · Basking Ridge, NJ +2

Senior AI Engineer at Verizon focused on building, optimizing, and deploying agentic AI/ML models and systems for customer-facing platforms. The role involves implementing LLM-powered solutions, integrating AI agent frameworks, optimizing inference pipelines, and collaborating on technical roadmaps and evaluations.

What you'd actually do

  1. Developing, testing, and scaling agentic AI/ML solutions, specialized workflows, and LLM-powered systems for VCG platforms.
  2. Integrating AI agent frameworks with existing customer success, digital, and retail channel technologies.
  3. Collaborating with product managers and GTS engineering teams to implement and iterate on production-grade technical roadmaps.
  4. Participating in engineering code reviews, technical design sessions, and red-teaming exercises to ensure safe and reliable model behaviors.
  5. Optimizing model inference pipelines, API endpoints, and data integration layers to meet high-performance consumer demands.

Skills

Required

  • Bachelor's degree or four or more years of work experience
  • Four or more years of relevant experience
  • One or more years of hands-on experience building and tuning AI/ML models or integrating LLM applications
  • Experience with software development methodologies (e.g., Agile)

Nice to have

  • A degree in Computer Science, Engineering, or a related field
  • Knowledge of standard AI/ML tooling, orchestration frameworks (e.g., LangChain, AutoGen), and software engineering best practices
  • Knowledge of systems and tools like ACSS, Optix, POS, CTI, WorkHub, Performance management Tools, existing AI integrations, and Verint
  • Experience with API design and development
  • Experience with cloud platforms (e.g., GCP, AWS, Azure) and cloud-native technologies
  • Strong organizational and prioritization skills and the ability to thrive in a dynamic environment, meet deadlines, and simultaneously work on multiple projects

What the JD emphasized

  • building and tuning AI/ML models or integrating LLM applications
  • architect pipelines and deploy models independently

Other signals

  • building agentic AI/ML models and systems
  • implementing next-generation customer success, sales, and digital agent solutions
  • optimizing model inference pipelines, API endpoints, and data integration layers