Cloud Engineer

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Company Overview

A fast-growing, early-stage healthcare technology company is transforming care navigation through AI-powered solutions. Founded by experienced leaders from major technology and healthcare organizations and backed by top-tier venture capital, the organization is focused on making it easier for patients to find the right doctors, helping providers prioritize patients who need care most, and improving access to healthcare while delivering stronger economic outcomes at scale.

Building on successful collaborations with health systems across the United States, the organization has expanded internationally into the MENA region, partnering with health systems to deploy its AI-powered care navigation platform.

The organization is hiring a hands-on Cloud Engineer to help architect, scale, and strengthen the infrastructure supporting its AI-driven healthcare platform.

This role will play a central part in engineering delivery, with responsibility for cloud infrastructure, Kubernetes platform reliability, CI/CD pipelines, and Bazel-based build systems. The Cloud Engineer will collaborate closely with backend and AI engineering teams to ensure systems are secure, observable, reliable, and capable of supporting real-time, production-grade healthcare workloads.

As a rapidly growing Series A company, the organization is looking for an engineer who can work across infrastructure architecture, release engineering, and production reliability. The role offers significant ownership and the opportunity to shape infrastructure strategy as the platform continues to scale.

Key Responsibilities

Infrastructure Architecture & Automation

• Design, build, and maintain cloud infrastructure in GCP using Terraform.
• Architect and manage Kubernetes (GKE) clusters across development, staging, and production environments.
• Improve networking, IAM, ingress architecture, and environment isolation.
• Build reusable infrastructure modules and eliminate configuration drift.
• Ensure infrastructure remains scalable, cost-efficient, secure, and production-ready.

CI/CD & Deployment Reliability

• Design and maintain CI/CD pipelines that enable safe and efficient deployments.
• Own and optimize Bazel build configurations, caching, and reproducibility.
• Improve build performance and developer productivity within a monorepo environment.
• Implement safe release strategies, including canary deployments, blue/green deployments, and rollbacks.
• Ensure environment parity and reduce deployment-related incidents.

Observability & Reliability

• Implement and improve logging, monitoring, and alerting across services and Kubernetes workloads.
• Establish SLIs and SLOs while driving ongoing reliability improvements.
• Reduce MTTR through improved system visibility and incident response processes.
• Improve production readiness standards and postmortem practices.
• Ensure infrastructure can support increasing AI workloads and real-time traffic.

Security & Compliance

• Strengthen IAM, secrets management, and least-privilege access controls.
• Harden Kubernetes clusters and cloud infrastructure against security risks and misconfigurations.
• Partner with security leadership to support HIPAA and SOC 2 compliance requirements.
• Improve auditability, change tracking, and infrastructure governance.
• Embed security best practices directly into CI/CD and build workflows.

Qualifications

Required

• 4–7+ years of experience in DevOps, SRE, or Infrastructure Engineering.
• Strong hands-on experience with GCP and Kubernetes, preferably GKE.
• Deep experience with Terraform and infrastructure-as-code practices.
• Experience building and maintaining CI/CD pipelines.
• Experience working with Bazel or similar build systems in production environments.
• Strong understanding of networking, IAM, and cloud security fundamentals.
• Experience supporting production systems with uptime and reliability requirements.

Nice to Have

• Experience supporting HIPAA or SOC 2 environments.
• Experience working in early-stage or high-growth startup environments.
• Familiarity with AI/ML infrastructure or real-time systems.
• Experience applying release engineering best practices in monorepo environments.

Disclaimer

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