Every build, test, and deployment our customers run costs us something. Right now we can see the top-line number — our AWS and Datadog spend — and we can see revenue. What we can’t see clearly enough is the line between them: which operations drive our cost of goods sold, how that changes as customers scale, and which changes would move it. If you’ve been in a similar role but have been frustrated by not being able to go super deep on this and model different categories/scenarios and costs then you’ll be able to scratch that itch here.
Cost questions arrive from the exec team as business questions, and today the answers get assembled part-time by people whose main job is something else. This role is designed to close this gap.
This is a hands-on engineering role, not a reporting one: you’ll own Buildkite’s cloud efficiency picture end to end — tracing COGS signals down to the tight loop technical drivers that cause them, building the models that explain them, then shipping or driving the changes that bring them down, and proving afterwards that the saving actually landed. You’ll report to the VP Engineering Platform and pair closely with him for your first month or two before running with substantial autonomy.
You’ll also partner with our CTO, Platform engineering, with the Data team who own the canonical COGS model, and with Finance on the FinOps side. The constraint that makes this interesting is that none of this work can come at the expense of reliability, throughput, or customer experience. Ultimately this role will help us with cost optimisation and directly driving growth through technical efficiency.
Cutting the bill is easy. But cutting the bill without anyone noticing except the CFO is basically the crux of the job.