Senior Software Engineer - AWS Cost Optimization

Heartflow•San Francisco, CA

6d•Hybrid

About The Position

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFR CT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFR CT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare. Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 750,000 patients worldwide. Heartflow is that rare company where massive commercial success meets deep clinical impact. We already have high-revenue, production-grade AI products backed by 15 years of rigorous research. We are leveraging our deep foundational AI expertise to add serious fuel to our high-growth fire. We are assembling a brand-new, dedicated team to pioneer production-grade Agentic AI systems within healthcare, fundamentally redefining clinical workflows and physician decision-making from the ground up. About the role(s) Are you a highly analytical software engineer passionate about building scalable tools, optimizing cloud compute infrastructure, and maximizing ROI? Do you thrive on writing elegant code to solve complex infrastructure, storage, and FinOps challenges? Join our dynamic Infrastructure Platform team and help us drive a critical initiative to ensure our modernized Kubernetes workflows and large-scale data systems are as cost-effective as they are powerful.

Requirements

8+ years of Software Engineering or Platform Engineering experience, with a proven track record of writing clean, scalable, and maintainable code in Python, Go, or Java.
Deep, hands-on experience with object storage APIs (AWS S3, Backblaze) and designing large-scale data transfer pipelines.
Proven experience building centralized client libraries, SDKs, or developer abstractions.
Experience building programmatic financial models, predicting cloud spend, and performing capacity planning for large-scale cloud migrations.
Ability to translate complex technical architecture changes into clear budgetary impacts.
Expert-level understanding of AWS billing, pricing models, enterprise discount programs, and scaling behaviors.
Strong hands-on understanding of Kubernetes (EKS) compute efficiency, alongside legacy services like Lambda and ECS.
Strong background using Terraform to deploy infrastructure and automations.
Excellent communication and technical leadership skills, with the ability to influence technical decisions across engineering, platform, and finance teams.

Nice To Haves

Experience developing Kubernetes operators or Custom Resource Definitions (CRDs) in Go.
Prior experience driving cost optimization and multi-petabyte data migrations simultaneously.
Experience with KubeCost, Finout, CloudHealth, or similar cloud-native FinOps solutions.
FinOps Foundation Certified Practitioner or Professional certification.
Experience working in a monorepo environment and establishing modern CI/CD practices for shared libraries.

Responsibilities

Architect and execute the large-scale, high-throughput migration of petabytes of data from AWS S3 to lower-cost alternative storage providers (e.g., Backblaze B2).
Design, develop, and maintain robust, centralized client libraries (SDKs) to abstract the underlying storage infrastructure, enabling application teams to seamlessly interact with object storage without vendor lock-in.
Partner closely with platform engineers to ensure the reference architectures for moving legacy workloads (AWS Lambda, ECS) to our target EKS clusters are cost-optimized by design.
Benchmark migrated services, right-size resource requests/limits, and develop strategies for Reserved Instances (RIs), Savings Plans, and Spot Instance utilization.
Develop, maintain, and refine sophisticated programmatic cloud capacity and spend models.
Forecast future infrastructure costs based on our Kubernetes migration roadmap, storage migrations, and traffic patterns, ensuring accurate budgeting and variance analysis in partnership with Finance.
Write custom software, automation scripts, and Kubernetes operators (using Python, Go, etc.) to enforce automated cost-control guardrails, resource tagging, and intelligent scale-down/cleanup for non-production environments.
Manage these guardrails via Infrastructure as Code (Terraform).
Implement and manage advanced cost observability telemetry (e.g., querying the AWS Cost and Usage Report (CUR) programmatically, KubeCost).
Build transparent, granular chargeback reporting into our internal developer platforms to empower individual engineering teams.