We're a small, fast-moving team solving one of the biggest challenges in modern AI infrastructure. Join us.
A few reasons people love working here.
Work from anywhere. We're distributed across the US.
Your work directly shapes the product and company direction.
Work with AI/ML, cloud-native, and real-time data systems daily.
Competitive compensation with meaningful equity.
We bias toward action, iterate quickly, and treat every release as an experiment.
Every decision starts with the customer's problem. We listen, measure, and adapt.
Open roadmaps, shared metrics, and honest conversations. No politics, no silos.
We're hiring across engineering, product, and go-to-market.
What you'll do: Design and ship the APIs that power real-time cost ingestion from AWS, GCP, and Azure billing exports. Build the GPU telemetry pipeline that processes 100M+ data points daily. Own the cost anomaly detection service end-to-end, from data modeling to alerting.
Day-1 scenario: A customer reports their GPU idle detection missed a cluster of 8x A100s sitting idle over a weekend. You trace it to a gap in our DCGM metric polling, fix the ingestion window, add a regression test, and deploy the fix — all before standup.
You bring: 5+ years Python, production FastAPI or Flask, PostgreSQL/BigQuery, cloud billing APIs (CUR, BigQuery Billing Export), experience with async data pipelines (Celery, Airflow). Bonus: GPU/ML infrastructure background.
What you'll do: Build the real-time cost dashboards that enterprise teams use daily. Implement interactive drill-down charts for GPU spend attribution, token cost breakdowns, and multi-cloud comparisons. Create the PR cost annotation UI that renders inline in GitHub.
Day-1 scenario: The PM flags that customers with 50+ cloud accounts are seeing 3s load times on the cost summary view. You profile the render path, implement virtualized table rows and query pagination, cutting load time to under 400ms.
You bring: 5+ years React/TypeScript, D3.js or Recharts, state management (Zustand/Redux), REST API integration, performance optimization. Experience with data-heavy dashboards and design system implementation.
What you'll do: Own the multi-cloud infrastructure that runs MetaFinOps — GKE clusters, Terraform modules, CI/CD pipelines, and observability stack. Design the tenant isolation model that lets us serve enterprise customers with strict data residency requirements (US, EU, APAC).
Day-1 scenario: An enterprise prospect requires EU data residency for GDPR. You spin up a new regional GKE cluster via Terraform, configure cross-region replication for shared config, and update the deployment pipeline to support region-aware routing — in one sprint.
You bring: 4+ years Kubernetes in production, Terraform IaC, GCP/AWS networking, GitHub Actions or ArgoCD, Prometheus/Grafana. SOC 2 compliance experience preferred.
What you'll do: Build the data backbone: ingest AWS CUR files, GCP billing exports, and Azure cost data into a unified cost model in BigQuery. Design Airflow DAGs that normalize, tag, and enrich cost records for 200+ cloud accounts. Power the ML anomaly detection models with clean, partitioned data.
Day-1 scenario: A new customer onboards 80 AWS accounts. Their CUR exports are 15GB/day with inconsistent tagging. You build an ingestion pipeline with deduplication, a virtual tagging layer that maps untagged resources to cost centers, and an Airflow DAG that processes the backfill in under 2 hours.
You bring: 4+ years data engineering, BigQuery/Snowflake, Airflow/dbt, Python, cloud billing data formats (CUR, BigQuery Billing Export). Experience with cost allocation and tagging strategies is a strong plus.
What you'll do: Own the product roadmap for the cost intelligence layer. Interview enterprise FinOps teams to understand their GPU cost attribution pain points. Write specs for the budget policy engine. Prioritize between shipping the Terraform cost preview vs. expanding Kubernetes namespace-level allocation.
Day-1 scenario: Three enterprise customers request conflicting features: team A wants Slack budget alerts, team B wants Jira ticket auto-creation on anomalies, team C wants custom dashboard widgets. You run a weighted scoring exercise, validate with usage data, and ship a phased plan that lands the highest-impact feature first.
You bring: 4+ years product management in B2B SaaS (infra, DevTools, or FinOps preferred), data-driven prioritization, SQL proficiency, experience writing technical specs, comfort with cloud billing concepts.
What you'll do: Design the interfaces that turn complex multi-cloud cost data into actionable insights. Create the dashboard experience for GPU utilization monitoring, the policy builder for budget guardrails, and the onboarding flow that gets customers from sign-up to first insight in under 10 minutes.
Day-1 scenario: User research shows that FinOps practitioners struggle to identify which AI models are driving cost spikes. You design a drill-down flow: cloud overview → GPU cluster → model → individual training job, with cost annotations at each level. You prototype in Figma, test with 3 customers, and iterate before handoff.
You bring: 3+ years product design for data-heavy B2B applications, Figma expertise, experience designing dashboards and data visualizations, understanding of design systems, ability to translate complex data into clear visual hierarchies.
What you'll do: Be the bridge between MetaFinOps and the developer community. Write hands-on tutorials showing how to integrate our API into Terraform workflows. Present at KubeCon and FinOps Foundation events. Build sample applications that demonstrate GPU cost tracking with real telemetry data.
Day-1 scenario: A popular ML engineering blog mentions "GPU cost visibility is still unsolved." You write a response post with a working code example using our Python SDK that tracks GPU idle time across a Kubernetes cluster, publish it within 48 hours, and it drives 200+ signups to our developer docs.
You bring: 3+ years developer relations or technical content creation, ability to write production-quality code in Python or TypeScript, conference speaking experience, active technical blog or social presence, understanding of cloud infrastructure and FinOps concepts.
What you'll do: Own the full enterprise sales cycle from prospecting to close for $50K-$500K ACV deals. Sell to VP Engineering, Head of FinOps, and CFO personas at companies spending $1M+ annually on cloud and AI infrastructure. Run technical demos showing ROI with real customer data.
Day-1 scenario: A Fortune 500 financial services firm is evaluating MetaFinOps against Vantage and CloudZero. Their pain: $4M/year in GPU costs with zero model-level attribution. You build a custom ROI model, coordinate a technical proof-of-concept with their DevOps team, and close a $180K annual deal by demonstrating 35% projected savings.
You bring: 4+ years enterprise SaaS sales ($50K+ ACV), experience selling to infrastructure/DevOps/FinOps buyers, MEDDPICC or similar qualification framework, track record of exceeding quota. Cloud infrastructure or FinOps domain knowledge strongly preferred.
We're always looking for exceptional people. Send us a general application and tell us what you'd bring to MetaFinOps.
Get in TouchJoin a team that's redefining how companies manage AI and cloud costs.
Apply Now