Back
Metro location and general mid-level platform skills increase applicant density, but niche observability focus moderates competition.
Observability and DevOps skills transfer broadly, but Azure and AI/platform context raise domain bias.
Requires specific observability tools and multi-discipline experience, but lacks strict years requirement.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and build the observability layer for a complex AI-driven event-based platform, focusing on Grafana dashboards for system health, performance, and behavior monitoring.
Design and implement instrumentation for metrics including AI-specific signals (e.g., LLM token consumption, inference timing) integrated with Azure Monitor and OpenTelemetry.
Serve as the subject matter expert on observability within the team, guiding dashboard development and enhancing team capability while supporting broader platform engineering efforts as needed.
Experience spanning at least two areas: software engineering, data engineering, and DevOps/platform engineering.
Hands-on experience building Grafana dashboards from real data sources.
Familiarity with Azure monitoring tools such as Azure Monitor or Application Insights.
Ability to understand and analyze complex distributed systems to identify critical observability metrics.
Engineer with breadth across software, data, and platform/DevOps domains to holistically understand distributed system behaviors.
Experience working with event-driven or microservices architectures to inform observability strategy.
Proficient in Python to navigate and contribute to the platform’s Nx monorepo codebase.