Job Description
Description :
Key Responsibilities and Deliverables :
– Design and build AI solutions for infrastructure validation and TRR automation, including a validation assistant for engineers.
– Develop intelligent automation that integrates with Azure DevOps (ADO) for pipelines, bug management, and workflow orchestration.
– Create AI/Copilot systems for predictive analytics and diagnostics across hardware.
– Build data ingestion and correlation pipelines across multi-source telemetry, logs, and firmware data to support RCA and compliance validation.
– Implement an AI-driven log analytics platform with intelligent notifications, anomaly detection, and guided remediation workflows.
– Deliver a bug automation engine integrated with ADO and a knowledge copilot to surface similar incidents, fixes, and best practices.
– Develop predictive failure detection and firmware compatibility analysis to reduce downtime and improve deployment readiness.
Required Skills & Qualifications :
– LLM engineering : Prompt engineering, retrieval-augmented generation (RAG), fine-tuning/evaluation, and safety/quality best practices.
– Log analytics, anomaly detection, and root-cause prediction models.
– Programming : Strong Python; C#, Powershell is a plus for infrastructure integration.
– AI/ML frameworks & cloud : Azure AI services, OpenAI; experience with PyTorch.
– Working with large-scale logs, telemetry, building reliable data pipelines.
– Familiarity with Azure DevOps, pipelines, and bug/incident management systems.
– Scalable AI system design, including API-based microservices architectures.
Preferred Domain Knowledge :
– Hardware validation and infrastructure; debugging workflows and failure analysis.
– Strong problem-solving and analytical thinking in high-scale, data-intensive systems.
– Ability to collaborate effectively with validation engineers, and infrastructure teams.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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