Platform Engineer

Blooming Health
Remote

About The Position

As we scale, we’re looking for an experienced and highly capable Platform Engineer to help build, secure, and scale the infrastructure powering Blooming Health’s rapidly growing platform. This is a US-based remote role with required overlap on EST hours. This Platform Engineer will play a critical role in strengthening the reliability, scalability, observability, and security of our infrastructure as the company enters its next phase of growth. Working closely with our existing DevOps and Engineering teams, this person will help mature platform operations, improve engineering enablement, and ensure our systems are built to support increasing scale, compliance requirements, and operational complexity. The ideal candidate is a strong technical self-starter who thrives in startup environments, communicates effectively across teams, and can quickly take ownership of infrastructure and platform initiatives in a fast-moving engineering organization.

Requirements

  • Strong hands-on experience with modern cloud platforms, including GCP and/or AWS. GCP experience is strongly preferred.
  • Deep experience building and managing infrastructure using Terraform and infrastructure-as-code best practices.
  • Comfortable writing and maintaining production-quality code and automation in Go, JavaScript, or TypeScript.
  • Experience helping startups scale infrastructure and operational maturity through periods of rapid growth and increasing system complexity.
  • Strong understanding of monitoring, logging, alerting, and production observability practices, including experience with tools such as New Relic.
  • Experience designing and maintaining secure, scalable production infrastructure with a strong understanding of operational reliability and engineering best practices.
  • Excellent written and verbal communication skills with the ability to clearly communicate technical requirements and collaborate effectively across teams.
  • Highly proactive, resourceful, and capable of independently driving technical initiatives in fast-paced environments.

Nice To Haves

  • Experience working within healthcare technology environments or supporting systems involving HIPAA, PHI, or regulated data is strongly preferred.
  • Familiarity supporting compliance-oriented engineering environments and collaborating with compliance or security stakeholders.
  • Experience working closely with distributed engineering and platform teams across multiple time zones.
  • Experience building internal tooling, deployment systems, and infrastructure workflows that improve developer productivity and operational efficiency.
  • Familiarity supporting infrastructure needs for AI/ML or data-intensive applications is a plus.

Responsibilities

  • Design, improve, and maintain scalable, reliable cloud infrastructure capable of supporting a rapidly growing SaaS platform and engineering organization.
  • Build and improve internal platform tooling, infrastructure automation, deployment workflows, and operational processes that increase engineering velocity and platform stability.
  • Manage and optimize cloud environments across GCP and/or AWS, ensuring systems are secure, cost-effective, scalable, and operationally mature.
  • Lead infrastructure automation efforts using Terraform and modern infrastructure-as-code best practices to improve consistency, reliability, and operational efficiency.
  • Improve monitoring, alerting, logging, and observability practices across the platform. Help establish proactive operational visibility and improve incident response processes using tools such as New Relic.
  • Partner with Engineering and Compliance teams to strengthen infrastructure security, support compliance requirements, and improve operational readiness for secure and regulated environments.
  • Work closely with Engineering, AI, and Product teams to support platform needs, improve developer workflows, and ensure infrastructure supports evolving product and AI initiatives.
  • Troubleshoot complex infrastructure and production issues, identify optimization opportunities, and proactively improve system performance, reliability, and scalability.
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