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# AI Platform Engineer

- **Company:** Verizon Communications Inc.
- **Location:** Loudoun County, VA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $101,000.0 - $194,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, BigQuery, Cloud Engineering, Cursor, Programming Tools, Open Source Technology, Systems Development Life Cycle, Rapid Prototyping Process, Azure Machine Learning, Software Engineering, Systems Integration, Google Cloud, GitHub Copilot, Retrieval-Augmented Generation, Open-source Models, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, AI Coding Agents, Agentic-AI, AI Platforms, Model Context Protocol, Network Server
- **Published:** October 4, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18527913?backUrl=%2Fcareer%2F18527913%2FAi-Platform-Engineer-Virginia-Ashburn

## About the Role

You get excited by the possibilities that technology creates and how it can improve people's lives. Applying your analytical skills and expertise to solve complex problems is personally rewarding. No stranger to working in a fast-paced environment, you convey a sense of urgency and balance multiple opposing priorities with ease, never missing a deadline.
You'll need to have:

 * Bachelor's degree or four or more years of work experience. *
 * Four or more years of of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
 * Experience in AI/ML software engineering, with deep proficiency in developing specialized frameworks.
 * Experience building MCP servers, tools, and integrations connecting LLM agents to internal systems.
 * Knowledge of IDE extension development (e.g., VS Code extensions) and developer workflow automation within modern SDLC pipelines.
 * Experience with developer AI tools like GitHub Copilot, Cursor, and Devin AI.

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

 * Experience implementing evaluation metrics, monitoring, and tracing using tools.
 * Experience with open-source models, LLMs, and fine-tuning techniques .
 * Experience implementing RAG pipelines, vector databases, and multi-agent frameworks (LangChain, LangGraph).
 * Knowledge of safety filtering, policy enforcement, and compliance governance for LLM deployments .
 * Experience designing and deploying scalable cloud infrastructure on Google Cloud Platform (GCP), utilizing key AI/ML services like Vertex AI, GKE, BigQuery, and Cloud Run .

 * Active contributions to open-source agentic frameworks, MCP servers, or developer tooling ecosystems .

## Description

Join Verizon as we continue to grow our industry-leading network to improve the ways people, businesses, and things connect. Within this broader mission of Verizon, our team provides cutting-edge AI tooling and capabilities to empower over 15,000 developers across the enterprise. We are seeking a highly skilled and innovative AI Engineer to focus on evaluating, fine-tuning, and deploying open-source models, LLMs, and foundational models, building agentic workflows, and integrating plugins and custom tools with developer platforms (such as GitHub Copilot, Cursor, Devin AI, and Google Antigravity) and our overall Software Development Life Cycle (SDLC). You will handle a wide variety of responsibilities pertaining to designing, building, and deploying AI solutions, agentic workflows, and MCP servers to improve developer productivity across Verizon.Key responsibilities include:

 * MCP Server & Tool Development: Design, build, and deploy Model Context Protocol (MCP) servers and tools to connect external APIs, internal enterprise tools, and data sources with AI coding agents.
 * Agentic Workflows: Develop and fine-tune agentic workflows and multi-agent architectures (using frameworks such as LangGraph or LangChain) to automate developer and SDLC tasks.
 * Prompt & Context Engineering: Apply advanced prompt design, context engineering, dynamic context injection, and hallucination mitigation strategies to maximize efficiency and accuracy.
 * Developer Tool Evaluation & Integration: Evaluate, test, and integrate AI developer tools (GitHub Copilot, Cursor, Devin AI, etc.) and IDE extensions (e.g., VS Code extensions) into the developer workflow.
 * Open-Source & LLM Optimization: Evaluate, fine-tune, optimize, and deploy open-source models and foundational LLMs tailored to enterprise needs and developer tools.
 * Rapid Prototyping & Research: Conduct fast-paced research and experimentation on emerging GenAI tools, preview features, and frameworks to keep our internal tools ahead of industry standards.