Senior DevOps Engineer — Remote, AWS/EKS Expert

Logoslabs; San Francisco (CA); Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Comprehensive healthcare (medical, 4-5

Job summary

Lyra Health is seeking a Sr. DevOps Engineer to design, implement, and maintain our cloud infrastructure and delivery pipelines. The role emphasizes modernizing platform tooling, a production EKS footprint, and optimized managed datastores.

You’ll automate infrastructure and improve developer experience across teams. The position is remote within the United States, with collaboration across engineering, data science, and ML teams.

Qualifications

• 5+ years in DevOps, SRE, or infrastructure roles on AWS.
• Experience with EKS and multi-tenant Kubernetes in production.
• Strong IaC using Terraform or OpenTofu.
• Experience creating CI/CD pipelines with GitHub Actions, Jenkins, or ArgoCD.
• Security governance and IAM policy enforcement in cloud platforms.

Responsibilities

• Design and implement infrastructure on AWS using Terraform/OpenTofu.
• Collaborate with engineering, data science, and ML teams to improve cloud infra.
• Build internal platform tools, templates, and self-service CI/CD pipelines.
• Automate infrastructure and operations tasks with scripting.
• Enforce cloud security, IAM policies, and compliance guardrails.
• Monitor performance and ensure availability and reliability.
• Remediate security vulnerabilities with engineers.

Skills

Public cloud experience

Collaboration

Tools

Terraform/OpenTofu

Kubernetes (EKS)

Helm

CI/CD (GitHub Actions/Jenkins/ArgoCD)

Python

Go

Bash

AWS services (EKS, SageMaker, EC2, etc)

Job description

Lyra Health is seeking a Sr. DevOps Engineer to design, implement, and maintain our cloud infrastructure and delivery pipelines. The role emphasizes modernizing platform tooling, a production EKS footprint, and optimized managed datastores.

You’ll automate infrastructure and improve developer experience across teams. The position is remote within the United States, with collaboration across engineering, data science, and ML teams.