Description

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

This role is on-site.

Responsibilities

• Design and implement RAG pipelines using chunking strategies, embeddings, vector search, and re-ranking.
• Productionize models and prompts with CI/CD, automated tests, canary releases, and SLOs for accuracy and cost.
• Build offline and online evaluation harnesses, golden sets, and tools for prompt and knowledge drift detection.
• Integrate GenAI tools with internal alarms, KPI platforms, ticketing systems, and inventory APIs.
• Collaborate with data engineering and platform teams to take use cases from discovery to production.

Required Skills

• 3–5 years of experience in AI/ML engineering or applied data science delivering production-grade solutions.
• Strong Python and SQL skills with mastery of large-scale telemetry and time-series datasets.
• Hands-on experience with Azure AI Search, Azure Machine Learning, and Azure OpenAI.
• Proficiency with CI/CD tooling, Git, and containerized deployments.
• Experience with RAG patterns: chunking, hybrid search, grounding with citations, and semantic caching.
• Ability to design system prompts, few-shot patterns, and structured outputs (JSON/JSON Schema).
• Understanding of LLM evaluation fundamentals: response quality, grounding, latency, and safety.

Preferred Skills

• Experience with agentic workflows, orchestration, and multi-step chains for automated diagnosis.
• Familiarity with GenAI frameworks like Semantic Kernel, LangChain, or LlamaIndex.
• Knowledge of 4G/5G RAN concepts, KPIs, and telecom standards (3GPP).

Key Skills

Education

Any Graduate