Gen AI Engineer

Create AI/Copilot systems for predictive analytics and diagnostics across hardware.\n4. Build data ingestion and correlation pipelines across multi-source telemetry, logs, and firmware data to support RCA and compliance validation.\n5. Implement an AI-driven log analytics platform with intelligent notifications, anomaly detection, and guided remediation workflows.\n6.

Deliver a bug automation engine integrated with ADO and a knowledge copilot to surface similar incidents, fixes, and best practices.\n7. Develop predictive failure detection and firmware compatibility analysis to reduce downtime and improve deployment readiness.\nRequired Skills & Qualifications\n\n1. LLM engineering: Prompt engineering, retrieval-augmented generation (RAG), fine-tuning/evaluation, and safety/quality best practices.\n2.

Log analytics, anomaly detection, and root-cause prediction models.\n\n3. Programming: Strong Python; C#, Powershell is a plus for infrastructure integration.\n4. AI/ML frameworks & cloud: Azure AI services, OpenAI; experience with PyTorch.\n5.

Working with large-scale logs, telemetry, building reliable data pipelines.\n\n6. Familiarity with Azure DevOps, pipelines, and bug/incident management systems.\n7. Scalable AI system design, including API-based microservices architectures.\nPreferred Domain Knowledge\n1.

Hardware validation and infrastructure; debugging workflows and failure analysis.\n2. Strong problem-solving and analytical thinking in high-scale, data-intensive systems.\n3. Ability to collaborate effectively with validation engineers, and infrastructure teams.