Our client, a leading multinational telecommunications technology company, has an urgent need for an AI Engineer.


Project overview: Verizon has launched a strategic AI transformation initiative to automate portions of its RF tower design (RFDS) process by embedding AI agents within its newly developed RFDA platform. The solution will leverage agentic workflow orchestration to analyze engineering requests, execute RF simulations, generate optimized tower design recommendations, and support human-in-the-loop decision making, with a phased adoption model progressing from AI shadowing RF engineers to fully autonomous execution.


Responsibilities:

•Implement bounded MOD scenario wrappers (5G NR add, LTE→NR / C-band, carrier add/remove, SNAP) inside the existing RFDS Agent (extends, does not fork).
•Co-author unit + integration tests against per-region golden MOD scenarios.
•Support late-Sep MODS soft pilot (1–2 Champions) — instrument, observe, triage.
•Take the lead during Oct Champions reverse-shadow for MODS and Nov wider rollout.
•Reinforce NB during cutover week (Aug 31 – Sep 5) and Sep hypercare as a second pair of hands.


If you would like to learn more, please reach out to

Required Skills

Required Skills:

•4–7 yrs production Python; at least 1 yr on LLM / agentic systems in production or near-production.
•Hands-on Google Vertex AI or transferable agent framework experience (Agent Builder, LangGraph, Bedrock Agents) demonstrated by shipped work.
•Comfortable extending an existing agent codebase rather than inventing one — disciplined enough to NOT spin up a new MCP server or a new KB partition when one already exists.
•Reads CLI / scripting API contracts cleanly and instruments them with structured logging + run-context.