Hi
Role: AI Engineer-MODS
Location: Remote
Duration: 6+ Month Contract
2 video interviews
Job Description
Must Have:
Current Telecom Project
client is embedding AI agents directly into its newly built RFDA platform to automate critical parts of the RF tower design (RFDS) process. You will help build agentic workflows that analyze engineering requests, run RF simulations, and generate optimized design recommendations, all while supporting a human-in-the-loop model that evolves toward full autonomy.
This is a high-visibility project with a clear roadmap and real deployment milestones. You will see your work go from pilot to production in a matter of months, with direct exposure to how large-scale telecom infrastructure decisions get made.
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.
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.
Should-have skills:
- MCP server contributor (extending, not just consuming).
- Test discipline - pytest, fixtures for synthetic external systems, golden-scenario regression patterns.
- RF / telecom adjacency.
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