Description

You will build and operate GenAI-powered tools to accelerate network troubleshooting, including triage assistants, KPI summaries, and anomaly detection.

Responsibilities

• Design and implement RAG pipelines with document preparation, embeddings, vector search, re-ranking, and citation strategies.
• Ship reliable services by productionizing models and prompts using CI/CD, automated tests, and canary releases.
• Implement evaluation and continuous monitoring via offline/online harnesses, golden sets, and drift detection.
• Integrate with internal systems such as alarms, KPI platforms, ticketing, and inventory APIs.
• Collaborate with data engineering and RAN SMEs to iterate on use cases based on measurable impact.

Required Skills

• 5+ years of experience in AI/ML engineering, data engineering, or applied data science.
• Strong Python and SQL skills for large-scale telemetry and time-series datasets.
• Hands-on experience with Retrieval-Augmented Generation (RAG) patterns, including chunking, hybrid search, and grounding.
• Experience with prompt design, structured outputs (JSON/JSON Schema), and function/tool calling.
• Production mindset with robust logging, monitoring, tracing, and observability practices.
• Understanding of 4G/5G RAN concepts and ability to translate network issues into KPIs.
• BS/MS in Computer Science, Electrical Engineering, Data Science, or equivalent practical experience.

Preferred Skills

• Experience with Azure ecosystem services including Azure AI Search, Azure ML, and AKS.
• Familiarity with GenAI frameworks like LangChain/LlamaIndex and MLOps/LLMOps practices.
• Background in building internal assistants or copilots for network operations or RCA.

Key Skills

Education

Any Graduate