Software Engineer, Cost Optimization (Infrastructure)

Kustomer•New York, NY

3d•$130,000 - $215,000•Remote

About The Position

Kustomer is looking for an Infrastructure Engineer to own cost optimization across our cloud and AI infrastructure. This role is mostly focused on driving down our AWS/infra and AI token spend, while keeping an eye on the AI tooling ecosystem that powers our platform. You'll sit on our Foundation team, partnering closely with engineering leadership to find, prioritize, and execute cost-saving initiatives without sacrificing performance or reliability. If you love digging into a cost and usage report, right-sizing EC2 fleets, negotiating reserved capacity, or figuring out why an LLM call is burning 3x the tokens it needs to; this role is built for you. This is a chance to own cost optimization as a function end to end; you'll set the strategy, build the tooling, and see it through from idea to impact.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
4+ years of experience with AWS infrastructure at scale, with a strong track record of driving down cloud costs
Hands-on experience with AWS cost tools (Cost Explorer, Cost and Usage Reports, Trusted Advisor, etc.) and EC2 right-sizing/reservation strategies
Proficiency with Terraform or other Infrastructure as Code tools, and a high-level programming language such as Go, Python, or JavaScript
You think in dollars saved, not just tickets closed

Nice To Haves

Familiarity with LLM/AI infrastructure cost drivers (token usage, model pricing, caching strategies) is a strong plus

Responsibilities

Own AWS cost optimization end-to-end: EC2 right-sizing, Reserved Instances/Savings Plans, spot usage, storage tiering, and unused resource cleanup
Build dashboards and reporting to track infra spend by team/service, and flag anomalies before they become expensive
Partner with engineering teams to identify and eliminate waste, think idle resources, over-provisioned instances, redundant environments
Drive architectural decisions that balance cost, performance, and reliability
Use Terraform to codify and enforce cost-conscious infrastructure standards
Analyze and reduce AI/LLM token spend across our AI-native platform, model right-sizing, prompt efficiency, caching, and routing strategies
Work with our Foundations team on developer tooling to build guardrails and observability around token usage
Evaluate deterministic vs. generative tool selection tradeoffs from a cost lens, and recommend where cheaper approaches can do the same job
Support Kustomer's AI capabilities (Architect, Concierge, Envoy) by keeping them performant and cost-efficient
Report on cost trends and savings opportunities directly to engineering leadership
Proactively identify systemic inefficiencies and build the tooling to keep them from creeping back
Collaborate with FinOps/finance stakeholders to forecast and track spend against budget, while driving alignment across engineering teams that balances developer input without sacrificing speed and momentum