Description

Key Responsibilities
​Architect and implement multi-agent workflows and LLM-powered agents for network anomaly detection, root-cause investigation, and triage.
​Build advanced RAG architectures using network incident logs, knowledge bases, and operational data.
​Lead prompt engineering, structured tool-calling, agent routing, and evaluation frameworks.
​Collaborate closely with enterprise architects, telecom data teams, and client stakeholders to operationalize AI capabilities.
​Core Technical Stack & Requirements
​GenAI / Agentic Frameworks: Hands-on expertise in Python, LangGraph, LangChain, Tool-calling agents, and Multi-agent orchestration.
​RAG & Search: Vector DBs (Pinecone, pgvector, OpenSearch), hybrid search, reranking, and embeddings.
​Domain Experience: Prior background in Telecommunications, Network Operations (NOC/OSS), or Anomaly Detection systems is strongly preferred.
​Cloud & MLOps: Solid working knowledge of AWS, Azure, or GCP AI/ML ecosystems, observability, and production deployment patterns

Key Skills

Education

Any Gradute