About The Role
We are looking for a DevOps Engineer-I to help manage and scale our cloud infrastructure and
deployment systems. You will work closely with the engineering team to automate deployments,
improve system reliability, and manage Kubernetes-based infrastructure.
As part of our platform evolution, you will also support AI-driven systems and data pipelines,
helping deploy and operate services that power AI/ML features.
This role is ideal for someone who enjoys automation, cloud infrastructure, Kubernetes, and
modern AI-enabled platforms.
Key Responsibilities / What You’ll Do:
● Manage and maintain Kubernetes clusters for production and staging environments.
● Deploy and manage applications using containerized infrastructure (Docker + Kubernetes).
● Build and maintain CI/CD pipelines for automated and reliable deployments.
● Manage cloud infrastructure (AWS/GCP) and ensure scalability, availability, and performance.
● Support deployment and scaling of AI/ML services, APIs, and data pipelines.
● Implement infrastructure to support AI workloads and model-serving systems.
● Monitor system health using observability tools (logs, metrics, tracing).
● Automate infrastructure provisioning using Infrastructure as Code.
● Troubleshoot infrastructure, networking, and deployment issues.
● Implement security best practices, secrets management, and access controls.
Experience & Qualifications:
● 1–3 years of experience in DevOps / Site Reliability / Cloud Engineering.
● Hands-on experience with Kubernetes (pods, deployments, services, ingress, scaling).
● Strong experience with Docker and containerized workloads.
● Experience with AWS or GCP cloud platforms.
● Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).
● Strong understanding of Linux systems and shell scripting.
● Familiarity with networking, load balancing, and distributed systems.
● Experience with monitoring and logging tools (Prometheus, Grafana, Datadog, CloudWatch,
etc.
Good to Have
● Experience deploying AI/ML services or model-serving frameworks.
● Familiarity with LLM infrastructure, vector databases, or AI APIs.
● Experience with Terraform or other Infrastructure-as-Code tools.
● Experience managing NGINX / ingress controllers.
● Experience with Helm charts.
● Exposure to data pipelines or ML workflows.
What We Offer
● Opportunity to work on scalable cloud infrastructure and modern AI-powered systems.
● Ownership of DevOps processes and infrastructure
● A fast-paced startup environment with high learning opportunities.
● Competitive compensation and growth opportunities.
