DevOps Engineer (AI Infrastructure)

About Us

We are a fast-growing digital agency building AI-powered products. Our AI team is expanding, and we are looking for a skilled DevOps Engineer to help us scale, automate, and secure our infrastructure.

Role Overview

You will be responsible for setting up and managing the CI/CD pipelines, infrastructure automation, and cloud environments that power our AI/ML workflows. This role is ideal for someone who thrives in fast-paced environments and is excited by the challenge of enabling scalable AI product delivery.

Key Responsibilities

• Design, implement, and maintain CI/CD pipelines for AI models, APIs, and supporting applications.

• Set up and manage cloud infrastructure (AWS, GCP, or equivalent) with a strong focus on scalability, cost optimization, and security.

• Support containerized environments using Docker and Kubernetes (EKS, GKE, etc.).

• Work closely with AI engineers and software developers to automate data pipelines, model training/deployment, and monitoring.

• Implement and maintain infrastructure as code (IaC) using tools like Terraform or Pulumi.

• Monitor system performance, troubleshoot production issues, and ensure system reliability and uptime.

• Enforce best practices in DevOps, security, versioning, and documentation.

Requirements

• 3+ years of DevOps, Site Reliability Engineering, or relevant infrastructure experience.

• Strong hands-on experience with cloud providers (AWS and GCP preferred).

• Solid understanding of CI/CD principles and experience with tools like GitHub Actions, GitLab CI, or Jenkins.

• Experience with Docker, Kubernetes, and container orchestration.

• Familiarity with IaC tools such as Terraform, CloudFormation, or Pulumi.

• Working knowledge of networking, security, and access control in cloud environments.

• Exposure to machine learning or AI deployment workflows is a strong plus.

• Comfortable collaborating with cross-functional teams including data scientists, backend engineers, and product managers.

Nice to Have

• Experience deploying AI/ML pipelines with tools like MLflow, Airflow, or Kubeflow.

• Understanding of GPU/TPU setup and auto-scaling strategies for training/inference workloads.

• Monitoring and logging using Prometheus, Grafana, CloudWatch, or similar tools.

Why Join Us

• Work on real AI products with tangible impact.

• Autonomy to shape and optimize our AI infrastructure.

• A collaborative and ambitious team, with leadership open to innovation and experimentation.

• Opportunities for growth and cross-disciplinary exposure across AI, web, and product development.