Cloud Operations Engineer AWS

Passionate about Scaling AI Deployment on Cloud ?

We are building the first NO-CODE AI PLATFORM for the AEC industry, with the 3rd generation Explainable AI, that allows users to create complex use cases with zero coding at the frontend and neuro-symbolic AI under the hood. We are deploying our platform on the cloud in a way that can scale across large number of data points.

Tasks

We are looking for a Cloud Operations Engineer to join our Bengaluru office.

You will be part of our Technology & Platform team and will work closely with our AI Engineers and Fullstack Developers to develop ML clouds and servers for deploying computer vision applications at scale.

• Design and further develop our AWS infrastructure using Terraform
• Deploy and scale containerised applications using Kubernetes
• Build AI Pipelines with Kubeflow and model serving frameworks such as KServe.
• Enable Self-Service and MLOps-DevOps best practices for Software and ML Engineers
• Use practices such as Infrastructure-as-Code (IaC), Continuous Delivery, Test-Driven Development and DevOps methodologies to establish a green-field cloud architecture, integrating IoT and edge devices
• Create tooling to automate workflows and ease day-to-day activities
• Ensure performance, security, scalability, maintainability, reliability and reusability

The technology will scale in public/private cloud across a rapidly increasing number of customers in multiple geographies, while processing and rendering large amount of based data points.

Requirements

• B Tech / M Tech in Computer Engineering from a top tier university
• Professional certifications in AWS
• Proven experience in cloud operations engineering on AWS
• Proven experience in the development of CI/CD pipelines (GitLab) and microservices within Kubernetes clusters
• Hands-on experience in designing, building and running scalable distributed infrastructure
• Deep knowledge and understanding of containerisation and the use of Docker and Kubernetes
• Expertise in AWS (especially Networking / VPN / EKS / IAM / Loadbalancer / Autoscaling)
• Solid experience in Python, Go
• Expertise in MLOps and experience with AI/ML tech stack (MLflow, Kubeflow)
• Proven experience with the Linux operating system and scripting (bash)