Description

Build, deploy, and operate GenAI-powered tools that 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.
• Productionize models and prompts using CI/CD, automated tests, canary releases, and monitoring for accuracy, grounding, latency, and cost.
• Implement evaluation harnesses for offline and online testing, including human-in-the-loop review and drift detection.
• Integrate with internal systems such as alarms, KPI platforms, ticketing, and topology APIs to close the loop from detection to remediation.
• Collaborate with data engineering and RAN SMEs to iterate use cases based on measurable impact like MTTR reduction.

Required Skills

• 3–5 years of experience in AI/ML engineering, data engineering, or applied data science.
• Strong Python and SQL skills; mastery with large-scale telemetry and time-series datasets.
• Hands-on experience with Azure AI Search for vector and hybrid search.
• Proficiency with CI/CD tooling and Git.
• Experience with RAG patterns including chunking, embeddings, and structured outputs (JSON/JSON Schema).
• Knowledge of prompt design, function/tool calling, and evaluation fundamentals.
• Understanding of production mindsets: logging, monitoring, tracing, security basics, and operational readiness.
• Solid understanding of 4G/5G RAN and mobility concepts (handovers, drops, KPIs).

Preferred Skills

• Experience with agentic workflows, orchestration, and LLMops practices like MLflow and OpenTelemetry.
• Familiarity with Azure ecosystem services including AKS, Event Hubs, and Data Factory.

Key Skills

Education

Any Graduate