Observability Engineer – New Relic Dashboards & Cost Metrics

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We are looking for an Observability Engineer to design and implement consolidated observability dashboards and cost metrics across a GenAI and compute environment. The role focuses on New Relic dashboarding, NRQL, cost and token-usage visibility, and transforming raw telemetry into governed, reusable aggregate metrics that provide both technical and business insights.

Our client is a large global enterprise operating across multiple markets, with a complex technology landscape and a strong focus on digital transformation and innovation. The organization is actively investing in modern cloud, data, and AI capabilities to enable scalable, secure, and highly automated solutions across its business.

The project is focused on building an enterprise-grade AI Agent Platform from the ground up. The platform will provide a standardized foundation for developing, deploying, orchestrating, securing, and observing AI agents across multiple teams and use cases.

The initiative covers the full agent lifecycle and brings together agent orchestration, observability, security, governance, integrations, evaluation, and platform engineering. Engineers joining the project will have an opportunity to influence key architectural and technical decisions and contribute to a new platform rather than maintaining an existing solution.

• Build and maintain New Relic dashboards using NRQL queries.
• Develop consolidated cross-tenant dashboards providing visibility into agent health, costs, and the overall estate.
• Implement cost and token-usage metrics for GenAI and compute workloads.
• Transform raw telemetry into governed, reusable aggregate metrics, ensuring appropriate lineage rather than simply replicating raw data.
• Define and maintain separation between technical and business observability, including metric derivation, replication, and linkage.
• Ensure strong metric facet hygiene, with consistent and low-cardinality dimensions.
• Support integration of observability metrics with downstream BI and analytics products where required.
• Contribute to ingestion and integration patterns using New Relic Metric API / Firehose and AWS cost-allocation data.

• New Relic dashboard building and NRQL queries

• Consolidated cross-tenant dashboards for agent health, cost, and estate overview

• Cost and token usage metrics for GenAI and compute workloads

• Deriving governed aggregate metrics from raw telemetry (with lineage, not raw copies)

• Technical vs Business observability segregation (derivation, replication, linkage)

• Metric facet hygiene (consistent, low-cardinality dimensions)

• 4+ years of observability engineering

• Dashboard and cost-metric implementation on New Relic (or equivalent SaaS observability)

• Translating raw telemetry into governed, reusable aggregate metrics

• New Relic Metric API / Firehose ingestion familiarity

• AWS cost allocation (Cost Explorer, tagging, per-account attribution)

• OpenTelemetry GenAI semantic conventions (gen_ai., pmi.agent.)

• Feeding a downstream BI/analytics data product