AI Observability Engineer

📋 Description Own tools, processes, and systems for AI observability across applications, platforms, and infra. Design, implement, and operate observability solutions for AI workloads (LLMs and agents). Configure AI tracing to capture latency, token usage, cost, quality, prompt analytics, model Develop internal tooling using Python for instrumentation and data collection. Build dashboards and monitoring with Grafana, Prometheus, and cloud observability platforms. Instrument AI platforms to provide health, usage, performance, and SLO visibility. 🎯 Requirements 5–8 years in observability, SRE, DevOps, or cloud engineering roles. Hands-on experience with Azure Monitor, Application Insights, Log Analytics, and Grafana. Experience with Langfuse, Grafana, and Prometheus for AI/app monitoring. Strong Terraform and CI/CD skills. Strong Python for automation, instrumentation, exporters, and tooling. Familiarity with ML workloads and AI observability requirements. 🎁 Benefits Competitive compensation package. Career development and continuous learning opportunities. Flexible working environment with ownership and autonomy. Opportunity to work on impactful AI infrastructure projects. Collaborative culture with international teams. Chance to contribute to next-gen AI platforms.