As a DevOps and Infrastructure Engineer, you will take ownership and create strategies, plans to manage deployments of our services, optimise, monitor and secure them. You will be working closely with our R&D and application teams to bring our AI services to our customers around the globe. These include AI multi-modal systems, core speech technologies and interactive digital avatars. Our core stack is a collection of services built on Linux with a focus on throughput and reliability, but we also have an Unreal Engine based Windows deployment. We handle two types of deployments: 1. World-wide cloud deployments to provide services to our SaaS business and 2. on-premises deployments with larger clients in case they need local deployments of our AI services.
We are looking for problem solvers, who have a passion for tackling challenging problems and coming up with practical solutions. You will be collaborating with a cross-functional team of talented scientists, engineers and designers who are equally driven. You should be eager to keep up-to-date with the latest technologies, aim to implement reliable, scalable and cost effective infrastructure. The sense for good monitoring and visualisation is equally important.
- Deliver high quality DevOps Deployment and Software solutions against tight schedules in an Agile/Scrum environment
- Design and implement monitoring solutions and logging management
- Manage and maintain our world-wide cloud infrastructure as well as our internal server infrastructure.
- Implement and maintain the Continuous Integration and Continuous Deployment pipeline
- General Sysadmin activities
- Minimum 2 years of DevOps related experience in industry
- Good knowledge of a cloud provider platform (e.g: HWC, AWS, GCP, ...)
- Excellent knowledge of Docker and Kubernetes
- Excellent knowledge of CI/CD
- Excellent knowledge of a scripted language (Python, bash, ...)
- Reasonable knowledge of a compiled language (Rust, C++, Go, ...)
- Familiar with Build, Configuration, Containerisation, Automation, Security, Migration, Management and Monitoring of Cloud platforms
- Troubleshooting skills and attention to detail
- Degree in Computer Science or similar
- Previous exposure to MLOps.
- Knowledge to manage large amount of data
- Commercial experience with SaaS infrastructures
- Passion for coding and basic understandings of AI/ML
- Familiarity with Windows deployments or deployments for server side rendering
- Knowledge of dev ops practices related to websockets, gRPC, WebRTC
- Experience with real time streaming systems