Offer summary

Qualifications:

Strong experience with Google Cloud Platform (GCP), Familiarity with Kubernetes, Helm, and CI/CD pipelines, Cloud certifications preferred but not mandatory, Knowledge of Python or Bash scripting.

Key responsabilities:

Design and manage GCP services for high-availability applications

Implement CI/CD pipelines and automate deployment processes

Job description

Description

We’re building next-generation AI-driven solutions to transform industries and enable smarter, data-driven decisions. We leverage cutting-edge cloud technologies to deliver scalable, secure, and high-performance applications. As we grow our innovative team, we are looking for a talented Cloud Engineer / DevOps Engineer who thrives in a dynamic, fast-paced environment and is eager to solve complex challenges. If you are passionate about cloud infrastructure, automation, and continuous integration/delivery, join us to help us build the future of AI-driven cloud applications.

Job Summary:

As a Cloud Engineer / DevOps Engineer at Lumana.ai, you will play a crucial role in designing, implementing, and maintaining the cloud infrastructure that powers our AI-powered applications. You will work closely with cross-functional teams to ensure the scalability, security, and reliability of our cloud-based systems. The ideal candidate will have strong expertise in Google Cloud Platform (GCP), CI/CD pipelines, and cloud management tools such as Kubernetes, Helm, and Kustomize. Additional experience with cloud-native services and tools like MongoDB Atlas, Twilio, SendGrid, and Redis will be a plus.

Key Responsibilities:

Cloud Infrastructure Management: Design, deploy, and manage Google Cloud Platform (GCP) services to support high-availability applications.
GCP expertise: Cloud Functions, Storage, Kubernetes Engine, VMs, and private link network management.
Set up and optimize large-scale ingress and egress traffic management, ensuring scalability and performance.
CI/CD Pipeline Management: Implement and maintain CI/CD pipelines using Codemagic and GitHub Actions to ensure rapid and reliable application delivery.
Automate build, testing, deployment, and rollback processes.
Optimize build and deployment times for greater efficiency.
Configuration Management: Use Kubernetes for container orchestration and deploy apps with Kustomize or Helm for templating and managing cloud-native configurations.
Administer and manage Kubernetes clusters, ensuring high availability and fault tolerance.
Optimize resource allocation and management for cost-efficiency in cloud environments.
Cloud Security and Compliance: Ensure cloud infrastructure is secure and compliant with best practices, including access control, identity management, and data protection.
Implement IAM (Identity and Access Management) and configure secure network policies.
Monitoring & Automation: Implement monitoring solutions for cloud infrastructure (e.g., GCP Monitoring, Prometheus, Grafana) and automate routine tasks such as scaling, failover, and backups.
Set up logging and alerting mechanisms to detect and respond to incidents proactively.
Database & Service Management: If you have experience with MongoDB Atlas, Redis, Kafka, and other cloud services, you will be responsible for configuring, maintaining, and optimizing these platforms.
Manage data pipelines and messaging queues.
Configure Twilio and SendGrid for communication services and email delivery.
Collaboration: Work closely with software engineers, product managers, and other stakeholders to improve system performance, security, and scalability.
Provide guidance on best practices for cloud architecture, infrastructure-as-code (IaC), and DevOps processes.

Requirements

Cloud Expertise: Strong hands-on experience with Google Cloud Platform (GCP), including services like GCP Storage, Cloud Functions, Kubernetes Engine, VMs, and private link networking.
GCP certification is preferred (Associate Cloud Engineer, Professional Cloud Architect).
CI/CD Pipeline: Solid experience setting up and managing CI/CD pipelines using Codemagic, GitHub Actions, or similar tools.
Proficient in automating build, test, and deployment workflows.
Containerization & Orchestration: Hands-on experience with Kubernetes for container orchestration and familiarity with Kustomize and Helm for configuration management.
Configuration Management Tools: Experience managing infrastructure using IaC tools like Kubernetes, Helm, and Terraform.
Cloud Database & Services (Plus): Expertise in managing cloud services like MongoDB Atlas, Redis, Kafka, Twilio, and SendGrid will be a significant advantage.
Networking & Security: Familiarity with large-scale ingress, egress, and private link network management in cloud environments.
Automation & Monitoring: Experience with cloud-native automation tools and monitoring systems (e.g., GCP Monitoring, Prometheus, Grafana).
VM Management: Experience working with VMs in cloud environments, including provisioning, scaling, and managing virtual machines.
Scripting and Programming: Proficient in Python, Bash, or other scripting languages to automate tasks and manage cloud resources efficiently.
Team Collaboration: Excellent communication and collaboration skills, with the ability to work in cross-functional teams.
Ability to work in an agile development environment with a focus on continuous improvement.

Preferred Qualifications:

Additional expertise in managing Kafka for stream processing or Okta for identity and access management.
Experience with serverless architectures in GCP (such as Cloud Functions).
Knowledge of cloud cost optimization strategies and best practices for reducing infrastructure costs while maintaining performance.
Familiarity with infrastructure monitoring and alerting platforms like Datadog or New Relic.
Experience working in Agile or DevOps environments.