DevOps Engineer

We are seeking a Senior DevOps Engineer to design, automate, and support our AWS cloud infrastructure and Kubernetes-based application platform. This role will focus on reliability, scalability, security, observability, and deployment automation across production environments., · Implement monitoring, dashboards, alerts, logs, metrics, and tracing using Datadog.

· Troubleshoot production issues and support incident response and root cause analysis.

· Participate in an on-call rotation to support production systems, respond to incidents, and assist with after-hours maintenance or escalations as needed.

· Improve CI/CD pipelines, release automation, and deployment reliability.

· Partner with engineering and security teams to improve infrastructure standards, operational readiness, and cloud security.

· Create and maintain technical documentation, runbooks, and operational procedures.

Interview Process:

• Interview #1: Video Screen with Talent Acquisition Team
• Interview #2: Video interview with the Hiring Manager (via MS Teams)
• Interview #3: Video interview with the Team (via MS Teams)

· 5+ years of experience in DevOps, Infrastructure Engineering, Site Reliability Engineering, Cloud Engineering, or a similar role.

· Strong hands-on experience with AWS cloud infrastructure.

· Production experience with Kubernetes, preferably Amazon EKS.

· Experience with Infrastructure as Code using OpenTofu, Terraform, or similar tools.

· Experience with Argo CD, Helm, and GitOps-based deployment workflows.

· Strong scripting or development experience with Python.

· Experience supporting Aurora PostgreSQL, ElastiCache Redis, and Amazon MQ for RabbitMQ in production environments.

· Experience with Datadog or similar observability platforms.

· Strong understanding of cloud networking, including VPCs, subnets, routing, security groups, DNS, TLS, ingress, and load balancing.

· Comfortable participating in an on-call rotation and supporting production incident response.

· Strong troubleshooting, communication, and collaboration skills.

Additional skills:

· AWS, Amazon EKS, Aurora PostgreSQL, ElastiCache Redis, Amazon MQ for RabbitMQ, AWS Load Balancers, IAM, VPC networking.

· OpenTofu, Terraform, Infrastructure as Code, Kubernetes, Helm, containers, ingress, services, ConfigMaps, Secrets, autoscaling.

· Argo CD, GitOps, CI/CD, release automation, Python, Bash or shell scripting, Datadog, metrics, logs, tracing, dashboards, alerting.

· Experience supporting high-availability SaaS or customer-facing platforms.

· Experience with Kubernetes autoscaling, ingress controllers, cluster upgrades, and resource optimization.

· Experience with backup, restore, disaster recovery, and capacity planning.

· Familiarity with AWS Well-Architected principles and cloud security best practices.

· Experience with GitHub Actions, GitLab CI, Jenkins, or similar CI/CD tools.

· Experience supporting message broker platforms such as RabbitMQ or Amazon MQ.

· AWS or Kubernetes certifications are a plus.

· Strong ownership mindset, operational discipline, and a passion for automation, reliability, and continuous improvement.

· Ability to communicate clearly with technical and non-technical stakeholders, with a willingness to mentor others.

Unleash your potential: What you will be doing and owning:

· Build and maintain AWS infrastructure using OpenTofu.

· Operate Kubernetes workloads on Amazon EKS.

· Manage GitOps deployments using Argo CD and Helm.

· Develop automation and operational tooling using Python and scripting languages.

· Support AWS services including Amazon EKS, Aurora PostgreSQL, ElastiCache Redis, Amazon MQ for RabbitMQ, load balancers, IAM, VPC networking, DNS, and security groups.

In-Office or Remote 7 Locations 155K-170K Annually Senior level In-Office or Remote 7 Locations 155K-170K Annually Senior level Design, automate, and support AWS cloud infrastructure and Kubernetes (EKS) platform. Build IaC with OpenTofu/Terraform, manage GitOps deployments with Argo CD/Helm, develop automation in Python, implement monitoring in Datadog, troubleshoot production incidents, participate in on-call rotation, and improve CI/CD, security, and operational readiness. The summary above was generated by AI

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