Software Engineer - Cloud FinOps & Reliability

Luma AI, Inc.•Palo Alto, CA

42d

About The Position

Luma's mission is to build multimodal AI to expand human imagination and capabilities. This requires a massive, reliable, and performant GPU infrastructure that pushes the boundaries of scale. Our SRE team is the foundation of our research and product velocity, and this role is a critical new function within it, dedicated to ensuring the financial efficiency of the supercomputer we are building. This is a foundational engineering position for a technical, data-driven expert who gets excited about optimization at a massive scale. As a foundational member of our SRE team, you will specialize in FinOps and cloud cost management, owning the financial health of one of the world's largest multi-cloud GPU infrastructures. You will be an SRE who applies a deep understanding of cloud architecture and pricing models to find and eliminate inefficiency. You will use your software engineering skills to build the tools and automation required to govern our cloud spend, providing critical insights that allow us to scale our AI research and products sustainably.

Requirements

You have 5+ years of experience in a technical role such as Site Reliability Engineer, DevOps Engineer, Infrastructure Engineer, or a dedicated Cloud Cost Engineer.
You have deep, hands-on expertise with the cost models and optimization levers of at least one major cloud provider (AWS, GCP), and a willingness to learn others.
You are proficient in Python for the purpose of scripting, data analysis, and building automation tooling.
You have a strong, foundational understanding of cloud infrastructure, including containerization (Docker, Kubernetes), networking, and storage.
You are not an accountant; you are a systems thinker who is passionate about applying engineering principles to solve financial challenges at scale.
You are a tenacious troubleshooter and a data-driven decision-maker who thrives on finding the "why" behind the numbers.

Nice To Haves

Experience managing a monthly cloud spend in excess of $1 million.
Relevant certifications, such as the FinOps Certified Practitioner (FOCP).
Experience building custom cost allocation, showback, or chargeback systems from scratch.
A background working with large-scale GPU clusters for AI/ML workloads.

Responsibilities

Analyze & Optimize: Actively monitor and analyze costs across our entire technical ecosystem-including multi-cloud infrastructure (AWS, GCP, OCI), on-premise clusters, and third-party services-to identify and execute on opportunities for cost optimization. Develop forecasting models to predict future spend and inform our capacity planning.
Manage & Commit: Develop and actively manage a multi-million dollar portfolio of Reserved Instances (RIs) and Savings Plans to maximize commitment-based discounts across our global GPU and CPU fleets.
Automate & Build: Apply a software engineering approach to design, build, and maintain custom tools and automation in Python and SQL. Your systems will track, analyze, and report on costs across our entire fleet of providers and services, with a focus on detecting anomalies immediately.
Partner & Advise: Working closely as an embedded member of the SRE team, you will partner with fellow SREs and research teams to model the cost implications of new models and infrastructure designs, providing expert guidance on cost-performance trade-offs.
Visualize & Report: Create and manage a centralized observability stack for cloud costs, building dashboards in tools like Grafana to give a real-time, granular view of our financial posture to all stakeholders.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume