AI Infra Engineer

Requirements

• ABOUT HEALTHLEAP HealthLeap builds AI that helps clinicians prioritize patients, surfaces the right data, and gets patients the care they need earlier, so they can leave the hospital sooner.
• Sequoia and First Round are backing us to build the platform that screens every patient for everything and drives tangible outcomes.
• Data flows through secure connections, transforms through data pipelines, and powers ML models that clinicians rely on every morning.
• You'll work alongside our data scientists and ML engineers to build and operate the infrastructure that makes this possible.
• WHY YOU You've built AI infrastructure at a startup where you owned everything.
• The person who set up the AWS accounts, wrote the Terraform, deployed the ML models, and debugged the VPN at 2am.
• WHAT YOU'LL DO - Deploy new hospitals: site-to-site VPNs, networking, container services, data pipelines - Build reliable data infrastructure that ingests, transforms, and serves data at scale (S3, Iceberg, Spark, Dagster, Airflow) - Partner with data scientists and ML engineers to productionize models and get them running reliably at scale - Own AWS infrastructure: multi-account orgs, ECS/EKS, Terraform, networking - Set up observability: monitoring, alerting, logging that actually helps debug issues -
• experience: networking, IAM, ECS/EKS, S3, and the rest - Solid with Terraform or similar infrastructure-as-code -
• Experience with data pipelines and orchestration (Dagster, Airflow, or similar) - You've operated production systems, not just built them - You figure things out, even when documentation doesn't exist NICE TO HAVE - MLOps
• experience: deploying and monitoring ML models in production - Healthcare data standards (FHIR, HL7v2) -
• Experience with Kubernetes, service mesh, or complex networking - Background at an early-stage startup where you owned infra end-to-end THIS ROLE IS NOT FOR YOU IF - Startup unpredictability feels like chaos to you.
• We care about deep work and deep rest (we have a minimum leave policy), but when a hospital go-live is on the line, we show up - even if that means a 60+ hour week. - You've only worked on platform teams at large companies.
• If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.

Benefits