Development operations Engineer

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Description

At Rime, we are on a massive mission to empower businesses and optimize our clients' operational processes. We operate a system that processes thousands of real-time video streams and sensor data, transforming them into critical operational insights. As a System Reliability Engineer (SRE), you will be the "backbone" ensuring the stability, speed, and reliability of our systems. Operating at the intersection of software engineering and operations (DevOps), you will ensure our servers and software run efficiently around the clock with minimal downtime, while guaranteeing seamless scalability as hundreds of new client branches are onboarded.

Requirements

1. CI/CD & Automation: Strong hands-on experience building and maintaining CI/CD pipelines using tools like GitHub Actions, GitLab CI, or Jenkins.

2. Infrastructure as Code (IaC): Deep practical experience with IaC tools, specifically Terraform or Ansible, along with strong knowledge of at least one major cloud platform (AWS, GCP, or Azure).

3. Security (DevSecOps): Experience integrating security testing (SAST/DAST) into pipelines and utilizing secure secrets management solutions (e.g., HashiCorp Vault, AWS Secrets Manager).

4. MLOps Knowledge: Familiarity with Machine Learning lifecycles, MLOps concepts, and the specific challenges of deploying AI and computer vision models into production.

Roles And Responsibilities

1. CI/CD Pipeline Automation: Design and build robust continuous integration and deployment (CI/CD) pipelines for backend services, frontend applications, and AI/Computer Vision models to ensure updates are released quickly and reliably.

2. Infrastructure as Code (IaC): Provision and manage cloud infrastructure using tools like Terraform or Ansible to ensure work environments are easily reproducible and highly scalable.

3. Developer Enablement (DevEx): Improve the developer experience by accelerating code build times, setting up efficient local development environments, and removing operational bottlenecks so engineers can focus entirely on writing code.

4. MLOps Collaboration: Work closely with the AI team to automate the lifecycle of machine learning models, from training and testing to seamless deployment in the production environment.

5. Security Integration (DevSecOps): Integrate automated security checks, vulnerability scanning, and secure secrets management into the deployment pipelines to ensure code security right from the start.