Salary: Competitive, based on experience
Work: Remote
Company Description
Qoves is on track to become the next consumer tech unicorn. With over 2.5 million followers across our platforms, we have built one of the largest global communities around beauty, aesthetics and AI. In only a short time, we have become one of the fastest growing consumer tech companies in the world, pioneering AI-driven facial analysis that is transforming the way people understand and improve their looks.
Our products range from consumer facial analysis reports to partnerships with leading clinics. We are scaling quickly, expanding our team and setting new standards in how technology and aesthetics intersect. This is your opportunity to join a company that is not just growing but reshaping an entire industry.
Role Description
We're looking for a skilled DevOps Engineer to join our team full-time on a remote basis. You'll own the reliability, scalability, and security of our AI platform infrastructure, building out our cloud-native deployment pipeline and ensuring our services run smoothly as we scale globally. Expect a fast-paced, high-autonomy role where your work directly underpins the performance and growth of the product.
Key Responsibilities
- Design, deploy, and manage Kubernetes clusters for production workloads, ensuring high availability and efficient resource utilisation
- Build and maintain CI/CD pipelines using GitHub Actions (or similar), automating testing, building, and deployment workflows
- Manage and optimise cloud infrastructure on AWS (EC2, EKS, ECR, S3, RDS, CloudFront) or GCP equivalents
- Containerise applications using Docker, maintaining image registries and optimising build processes
- Implement infrastructure as code using Terraform, Pulumi, or CloudFormation to ensure reproducible and version-controlled environments
- Monitor system health and performance using observability tools (Prometheus, Grafana, Datadog, or similar), setting up alerting and incident response processes
- Manage and secure PostgreSQL databases in production, including backups, replication, and disaster recovery
- Harden infrastructure security, manage secrets, IAM policies, network segmentation, and compliance best practices
- Collaborate closely with backend engineers to streamline deployments of Python (FastAPI/Django) services
- Drive cost optimisation across cloud resources, right-sizing instances and managing reserved capacity
- Own incident response and post-mortem processes, driving reliability improvements across the platform
- Support the integration and deployment of AI/ML workloads, ensuring GPU and compute resources are efficiently provisioned
Qualifications
- 3+ years of professional DevOps, SRE, or platform engineering experience
- Demonstrated hands-on Kubernetes experience in production environments, including cluster provisioning, pod orchestration, Helm charts, service meshes, and troubleshooting at scale
- Strong proficiency with Docker and container orchestration
- Solid experience with at least one major cloud provider (AWS preferred, GCP also accepted)
- Proficiency with infrastructure as code tools (Terraform, Pulumi, or CloudFormation)
- Experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar)
- Familiarity with monitoring and observability stacks (Prometheus, Grafana, Datadog, ELK, etc.)
- Working knowledge of Linux systems administration and networking fundamentals
- Experience managing PostgreSQL or other relational databases in production
- Understanding of security best practices
- Scripting skills in Python, Bash, or Go for automation tasks
- Self-starter who thrives in fast-paced environments with a high degree of ownership and autonomy
Nice to Have
- Experience deploying and managing AI/ML inference workloads (GPU provisioning, model serving)
- Familiarity with Supabase, Firebase, or similar BaaS platforms
- Experience with service mesh technologies (Istio, Linkerd)
- Contributions to open-source infrastructure or DevOps tooling
- AWS or GCP professional certifications
Why Work at Qoves
- Solve real problems using cutting-edge AI technology
- Well-funded startup with 2.5M+ community and strong market traction
- High autonomy and ownership over infrastructure direction
- Work directly with founders in a meritocratic, mission-driven culture
- Shape the future of an entire industry at the intersection of AI and aesthetics
