Website:
nexus-aidc.com
Job details:
Company Description NEXUS is building the Data Center Operating System for the AI era: a single software control layer that unifies orchestration, full stack observability, FinOps, and intelligent workload analytics with a real time digital twin at its core. We don't build hardware and we don't train models. We build the layer that makes hyperscale AI infrastructure visible, predictable, and economically sustainable.
Role Description We are hiring an autonomous, highly driven Principal FinOps Analyst to serve as the definitive subject matter expert on AI infrastructure economics, workload cost attribution, and resource efficiency. In this strategic, high-impact role, you will operate squarely at the convergence of multi-cloud billing systems, infrastructure telemetry, data center operations, container orchestration, and enterprise corporate finance.You will be responsible for synthesizing data across major cloud cost management ecosystems including AWS Cost Explorer/CUR, Azure Cost Management, Google Cloud Billing, and Oracle Cloud Infrastructure Cost Management alongside high-frequency time-series telemetry. This includes facility power metrics (kWh, PUE), physical infrastructure dynamics, Kubernetes namespace allocations, and GPU utilization (via DCGM exporters and VRAM footprint). You will transform these data streams into automated financial attribution models, showback and chargeback frameworks, and real-time cost guardrail engines for enterprise customers and hyperscale AI infrastructure providers.
As a Principal Finops Analyst, you will
- Architect granular unit-cost models that map compute spend across native cloud platforms and bare-metal infrastructure directly to AI outputs (e.g., Cost per 1M Tokens Processed, Cost per Training Epoch, and Cost per Active Inference Tenant).
- Analyze, normalize, and ingest complex cost data from hyperscaler billing platforms including AWS Cost Explorer / CUR, Azure Cost Management, GCP Cloud Billing, and Oracle Cloud Infrastructure (OCI) Cost Analysis into unified financial models.
- Incorporate facility-level power metrics (kW/h per rack, PUE), thermal efficiency, and physical server depreciation schedules directly into virtualized and containerized compute cost baselines.
- Build namespace, pod, and container-level cost-allocation models in Kubernetes, analyzing the financial gap between CPU/memory requests versus actual usage to optimize bin-packing efficiency.
- Design algorithms to detect silent capital drain and idle hardware overhead across multi-cloud and hybrid environments, including unutilized GPU VRAM, unassigned tensor cores, and over-provisioned inference headroom.
- Correlate infrastructure cost drivers directly with application performance telemetry (APM, latency SLAs, request throughput) to help executive teams balance performance with cost optimization.
- Architect automated showback and chargeback systems for multi-tenant enterprise IT, cloud service providers, and sovereign infrastructure operators.
- Implement real-time cost anomaly detection rules, budget enforcement thresholds, and automated guardrail policies to prevent resource waste before invoices are generated.
- Leverage advanced AI tools to accelerate telemetry analysis, model complex multi-cloud infrastructure cost scenarios, and generate executive-ready financial reporting.
Required Qualification
- 3+ years of professional tenure in FinOps, Cloud Financial Management, or Infrastructure Economics across enterprise, hybrid, or high-density compute environments.
- Hands-on proficiency analyzing and navigating native public cloud billing platforms and cost explorer systems (AWS Cost Explorer / CUR, Azure Cost Management, GCP Cloud Billing, OCI Cost Management).
- Advanced proficiency with observability platforms and time-series data ecosystems (Prometheus, Grafana, OpenTelemetry, SQL, or ClickHouse).
- Practical understanding of container cost allocation mechanisms, Kubernetes scheduling, resource requests/limits, and multi-tenancy models.
- Solid conceptual grasp of modern GPU server architectures (e.g., NVIDIA HGX/DGX, H100/B200 clusters) and hardware telemetry exporters (e.g., DCGM).
- A proactive willingness to seamlessly integrate advanced AI engineering and analytical tools into daily workflows to optimize output velocity.
Preferred Qualification
- FinOps Certified Practitioner (FCP) or FinOps Certified Architect designation.
- Hands-on experience working with hyperscaler marketplace billing, committed use discounts (AWS Savings Plans/RIs, Azure Reserved Instances, GCP CUDs, OCI Annual Commitments), or enterprise billing APIs.
- Direct operational exposure to DCIM platforms, power usage metrics (kW/h, PUE), or facility-level thermal dynamics in data center environments.
- Hands-on experience working with container cost frameworks (e.g., OpenCost, Kubecost concepts) or automated cloud rightsizing engines.
- Basic script writing agility using Python, SQL, or shell scripts to automate data validation, cost model transformations, or custom API integrations.
Why Now
NEXUS is expanding globally. We are actively scaling our footprint across four critical theatres - North America, the GCC, Asia-Pacific, and Europe and we are hiring exceptional engineering, operational, and leadership talent to drive our organization forward. If you are an autonomous, high-conviction professional who wants your next decade of work to sit at the intersection of AI, infrastructure, and enterprise software at the precise moment the market is being decided - we want to talk to you.
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