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Distinguished Engineer - Applied AI Solutions

Job in Alpharetta, Fulton County, Georgia, 30022, USA
Listing for: Verizon
Full Time position
Listed on 2026-09-04
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below

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...

Verizon is building one of the most advanced autonomous networks in the industry. We are looking for a Distinguished Member of Technical Staff to join our team to architect & build the applied AI layer behind that autonomy.

You will own the design of Gen AI-powered systems — spanning LLMs, agentic frameworks, and all three major cloud providers, from the data center to the edge — that turn Verizon's infrastructure into intelligent, self-defending, self-optimizing platforms. You will implement Generative AI solutions across our Standard Operating Environment that enable applied AI solutions for products and services.

This is a builder's role for a technical leader who wants to work at the frontier of applied AI and autonomous networking — backed by the scale of Verizon.

The key responsibilities include:

  • Designing, building, and deploying applied AI/Gen AI solutions on Verizon's Gen AI platform to support Network and product use cases.
  • Partnering with Network and product teams to identify high-value use cases and translate them into scalable AI-driven solutions.
  • Evaluating and integrating large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering, fine-tuning, and agentic AI frameworks into production systems.
  • Architecting and deploying AI workloads across AWS, Azure, and Google Cloud Platform, selecting the right cloud services for performance, cost, and scale.
  • Collaborating with cross-functional engineering, data science, and product teams to streamline the AI solution development lifecycle.
  • Establishing best practices for model evaluation, responsible AI, security, and governance across Gen AI deployments.
  • Mentoring engineers and acting as a technical thought leader on Gen AI adoption across the organization.

What we're looking for...

This position will help drive innovation, operational efficiency, and customer experience by applying Generative AI capabilities to real-world Network and product challenges.

You'll need to have:

  • Bachelor's degree or four or more years of work experience.
  • Eight or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
  • Strong familiarity with Generative AI concepts, including LLMs, prompt engineering, RAG, embeddings, fine-tuning, and agentic/multi-agent architectures.
  • Proven experience building and deploying cloud-based solutions across all three major cloud providers (AWS, Azure, and GCP).
  • Experience with on-premise AI inference at the edge, including deploying and optimizing models in resource-constrained, low-latency, or disconnected environments.
  • Strong security background, with the ability to design and implement security guardrails for AI products and platforms as AI-related security threats continue to increase (e.g., prompt injection, data leakage, model abuse, adversarial inputs).
  • Strong problem-solving abilities along with verbal and written communication skills.

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

  • A Master's degree in Computer Science or related technical field.
  • Experience with Gen AI platforms and tools (e.g., Amazon Bedrock, Google Vertex AI, Lang Chain, or similar frameworks).
  • Experience with MLOps/LLMOps practices, including model monitoring, fine tuning, evaluation pipelines, and CI/CD for AI systems.
  • Knowledge of cloud architecture across AWS, Azure, and/or GCP.
  • Demonstrated experience leading technical projects or mentoring engineering teams.
  • Ability to synthesize project findings and translate…
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