AI Engineer (Agentic AI Platform) — S1

Role Overview

An agent on the telecom network gets asked for a subscriber's Wi-Fi password. The right technician gets it. An unauthorized queue doesn't. Context and identity decide in real time - that's the platform we're building. We're looking for engineers who can own the architecture, not just implement it. You'll go deep on one or two of the following workstreams: Orchestration, Grounding, Interop, Trust, or Exploration.

Responsibilities

• Orchestration: multi-agent engines, reasoning loops, query planning/rewriting, short- and long-term memory
• Grounding: knowledge graphs, identity graphs, ontology mapping to telecom taxonomies, text-to-SQL over undocumented schemas, RAG over legacy PDFs
• Interop: A2A-compliant agent design, containerized MCP servers, third-party A2A integrations
• Trust: contextual guardrails, RBAC policy, tracing, and evals wired into CI
• Exploration: POCs on new frameworks, evaluated against the A2UI/AGUI landscape
• Making legacy provisioning systems answer questions, writing evals that catch regressions, and debugging non-deterministic systems.

Requirements

• Production-level Python experience
• Hands-on experience with real LLM systems in production (RAG, tool-calling agents, or orchestration)
• Docker and Kubernetes
• Strong SQL — able to design schemas, not just query them
• Willingness to learn telecom domain knowledge
• Comfort working with immature tooling and debugging framework-level issues

Skills

• Python
• GCP
• Docker
• LangChain
• SQL

Benefits

• Commuter assistance
• Flexible schedule
• Health insurance
• Paid sick time
• Paid time off
• Work from home