Description

Build and operate GenAI-powered tools to accelerate network troubleshooting, including triage assistants, KPI summaries, and anomaly detection with source citations.

Responsibilities

• Design and implement RAG pipelines, managing document chunking, embeddings, vector search with re-ranking, and grounding strategies.
• Ship reliable production services by integrating CI/CD, automated tests, canary releases, and monitoring for accuracy, latency, and cost.
• Implement evaluation harnesses for offline and online testing, including golden sets, human-in-the-loop review, and drift detection.
• Integrate GenAI outputs with internal alarms, KPI platforms, ticketing systems, and topology APIs to close the loop from detection to remediation.

Required Skills

• Python and SQL proficiency for building reliable data transformations.
• Experience with Azure OpenAI, Azure AI Services, and Azure Databricks.
• Hands-on work with Spark for large-scale telemetry and time-series datasets.
• Strong understanding of GenAI patterns: RAG, prompt design, function calling, and structured outputs.
• Knowledge of evaluation fundamentals: response quality, grounding, safety, and cost controls.
• Experience with production mindset practices: logging, tracing, observability, and security basics.
• BS/MS in Computer Science, Electrical Engineering, Data Science, or equivalent practical experience.
• 5+ years of experience in AI/ML engineering or applied data science.

Preferred Skills

• Experience with agentic workflows, orchestration, and MLOps/LLMOps practices.
• Familiarity with telecom standards (3GPP) and RAN concepts (4G/5G mobility, KPIs).
• Experience building internal assistants for network operations or RCA.

Key Skills

Education

Any Graduate