Senior DevOps Engineer

About the role

Lyra Health, a provider of evidence-based mental health care, is looking for a Senior DevOps Engineer to design, implement and maintain its cloud infrastructure and support its software delivery pipelines. The role focuses on modernizing platform tooling, evolving the production Elastic Kubernetes Service (EKS) footprint and optimizing managed cloud datastores (AWS RDS, Aurora, ElastiCache). It is a remote position open to candidates residing in the United States.

Key responsibilities

• Design and implement infrastructure on AWS using Terraform/OpenTofu, Python and Kubernetes.
• Build, maintain and abstract internal platform tools, developer templates and self-service CI/CD pipelines, applying a software product mindset.
• Automate infrastructure and operations tasks with scripting languages.
• Operationalize cloud security: enforce continuous vulnerability remediation, strict IAM policies and compliance guardrails within platform pipelines, and work with engineers to remediate security vulnerabilities.
• Monitor system and network performance and take proactive steps to keep infrastructure available and reliable.
• Enforce IAM processes and tools that comply with data privacy and protection regulations.

Required profile

• 5+ years in a DevOps, SRE or infrastructure role focused on public cloud environments (AWS required).
• Hands-on experience administering, scaling and troubleshooting multi-tenant Kubernetes (EKS) environments in production.
• Strong coding skills in Python, Go or Bash for automation scripts and integrations.
• Effective communication, independent and collaborative work, and strong problem-solving and troubleshooting skills.

Required skills

• AWS: EKS, SageMaker, EC2, ECS, VPC, IAM, KMS, RDS, ELB/ALB, MWAA, Identity Center
• Infrastructure as code with Terraform or OpenTofu, and Helm templates and packages
• CI/CD pipelines with GitHub Actions, Jenkins and/or ArgoCD
• Preferred: cluster autoscaling (e.g. Karpenter), cost optimization, logging analysis and performance tuning, self-service developer tooling, and ML/data science workloads (SageMaker)