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ClinicallyAI

DevOps Engineer

San Diego, CAUnited States
FullTime · Engineering | Development
POSTED 13 AUGVERIFIED 1D AGO
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Role
87 days opentrue age
Posted 13 Aug
Pay
$88k–$132kno pay posted
Market p25–p75
$88k–$132k
San Diego · n=3 · 365d to 4 Nov
CompanyClinicallyAI →
14open roles
Opened · 30d
+0
Closed · 30d
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7d of snapshots · 30d window
Market
3,288open · DevOps / SRE / Infra
Opened · 7d
+2066% of open
All devops / sre / infra
7,040open
All tracked boards · live 9 Nov · n=3,288
GCPKubernetesDockerTerraform

About Clinically AI

Clinically AI is a rapidly scaling healthcare AI company transforming how behavioral health and healthcare organizations manage clinical documentation, compliance workflows, chart auditing, and operational efficiency through artificial intelligence.

Our platform helps clinicians, compliance teams, administrators, and healthcare organizations reduce administrative burden, improve documentation quality, strengthen audit readiness, and operate more efficiently. We operate at the intersection of AI, healthcare operations, workflow design, and real-world clinical execution, where security, reliability, scalability, and performance matter.

The Opportunity

We are seeking a DevOps Engineer to own and evolve the infrastructure, deployment systems, and cloud environments that power Clinically AI's product platform.

This is a hands-on engineering role for someone who thrives in modern cloud-native environments and enjoys solving complex infrastructure, reliability, security, and deployment challenges. You will work closely with Backend Engineering, AI, Product, and Engineering leadership to build and maintain the infrastructure that supports browser extensions, mobile applications, backend services, real-time AI processing, data pipelines, and customer-facing applications.

You should be comfortable operating with significant ownership and autonomy across GCP, Terraform, Helm, Kubernetes, CI/CD, observability, and containerized architectures. As we scale, you will have the opportunity to influence infrastructure strategy, deployment practices, security standards, and engineering culture.

What You'll Own

Design, build, and maintain cloud infrastructure on GCP, with a focus on GKE, container orchestration, and secure multi-environment deployments.

Build and maintain Infrastructure-as-Code using Terraform to ensure infrastructure is reproducible, versioned, and automated.

Develop and maintain Helm charts for consistent service deployments, upgrades, rollbacks, and environment management.

Improve and optimize CI/CD pipelines using GitHub Actions to support reliable deployments across staging, beta, and production.

Partner with engineering leadership to design scalable infrastructure for new services, AI pipelines, and high-throughput workloads.

Implement robust observability across logging, metrics, tracing, alerting, and system health.

Drive infrastructure security best practices, including secrets management, least-privilege IAM, zero-trust patterns, and compliance alignment.

Optimize infrastructure performance, reliability, and cost while maintaining strong availability and security requirements.

Participate in on-call rotations, incident response, and post-incident reviews to continuously improve platform reliability.

Partner closely with Backend, AI, and Product teams to support new features, data pipelines, and infrastructure requirements as the platform grows.

What We're Looking For

Cloud-Native Infrastructure

You have strong experience building and operating modern cloud infrastructure and understand how to design secure, scalable, and reliable environments for production software.

Infrastructure as Code

You are highly comfortable with Terraform and believe infrastructure should be reproducible, version-controlled, automated, and maintainable.

Kubernetes & Containerization

You have hands-on experience with production Kubernetes environments, containerized applications, and the broader Kubernetes ecosystem.

Deployment & Automation

You understand how to build reliable CI/CD systems that allow engineering teams to move quickly without sacrificing stability, security, or quality.

Reliability & Observability

You think proactively about system health, monitoring, alerting, incident response, performance, and reliability rather than simply reacting when systems fail.

Security & Ownership

You understand infrastructure security fundamentals and take ownership of the systems you operate. You are comfortable identifying problems, making decisions, and improving systems without needing constant direction.

Source · ClinicallyAIFirst seen 4 NovOriginal ↗