Llm Cost Telemetry Engineer Jobs

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FinOps AI Data Engineer, Principal

PG&E Corporation Oakland, CA

Oakland, CA

Today

$140k - $238k/yr Full time Manager Analytics Artificial Intelligence

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Job Description

The FinOps AI Data Principal at PG&E Corporation will design, build, and scale the core FinOps Data Platform to provide governed visibility into cloud and generative AI consumption. The role focuses on data pipelines, models, and reporting that support showback/chargeback readiness, forecasting, anomaly detection, unit economics, and optimization insights.

Responsibilities

Build and enhance the FinOps dataset, data model, reporting pipeline, and AI usage and cost telemetry integrations.
Convert billing and usage requirements into scalable data and reporting capabilities, including allocation, tokenomics, AI Gateway, AI DLC Tool, AI Agent Tool, LLM, workspace, user, AppID, use-case, order-number, model-provider, and model-name.
Support mandatory metadata ingestion, FinOps Data Lake integration, FOCUS-aligned AI data modeling, full-cost showback dependencies, and AI chargeback reporting foundations.
Standardize, simplify, and automate FinOps reporting, AI showback and chargeback views, optimization insights, anomaly detection inputs, and related process workflows.
Increase data engineering capacity across Snowflake, PowerBI, Flexera, AI Gateway, external AI usage sources, and cloud provider cost data pipelines.
Build and maintain AI usage telemetry and tokenomics datasets, allocation logic, unit economics inputs, and AI showback and chargeback reporting foundations.
Automate data quality checks, reporting refresh cycles, anomaly detection inputs, optimization insight pipelines, and consumption trend datasets for cloud and AI spend.
Support inventory and data capture for LLM usage outside the Enterprise AI Gateway, including known external GenAI and SageMaker use cases.

Requirements

BA/BS in computer science, management information systems, or a related field, or equivalent work experience.
10 years of experience across multiple data engineering and ETL ecosystems.
3 years of experience in machine learning algorithm deployment and machine learning operations.
Experience leading development teams.
5+ years of experience building production-grade, distributed data pipelines.
Deep knowledge of multi-cloud billing mechanics, including AWS CUR and Azure FOCUS datasets, along with FinOps Framework principles.
Proven experience tracking and modeling AI infrastructure costs, including LLM API usage, GPU clusters such as NVIDIA Triton and Kubernetes, and vector database spend.
Hands-on experience with cloud data warehouses and lakehouses such as Snowflake, Databricks, BigQuery, or Amazon Redshift.
Strong background in designing schemas for complex financial allocation, amortization, shared-cost showback, and forecasting.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field; FinOps Foundation Certified (FOCUS) and a professional designation are desired.

Core Technologies

Snowflake, PowerBI, Flexera
AI Gateway, NVIDIA Triton, Kubernetes
Vector database, Databricks, BigQuery, Amazon Redshift
AWS CUR, Azure FOCUS datasets
FOCUS, LLM, SageMaker, GenAI
FinOps Framework

Role Details

Location: Oakland, CA (hybrid)
Business unit: Technology & Security
Job category: Information Technology
Job level: Manager/Principal
Work type: Hybrid
HQ location: Flexible within the Bay Area Region, agreed upon by the hiring leader and the successful candidate
Hybrid working: Hybrid working from your remote office and in-person at the Oakland Corporate Office 1-2x per week, or based on business needs or company requirements

Compensation

Salary range: USD 140,000 - 238,000 per year

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