Are you looking for a challenging yet rewarding project that will leverage the best of your decision-making and engineering excellence?

At DIAL we strive to maintain a delicate balance between the constantly evolving LLM landscape, the demands and scales of enterprise customers, and the restrictions that come with developing an open-source multimodal LLM and Application Orchestration platform under the Apache 2 license, all while ensuring ease of use and deployment and constantly delivering new features.

Using DIAL as a foundation, we build a variety of practical solutions that can be customized for specific needs, such as StatGPT, a talk-to-your-data platform adopted by the International Monetary Fund and World-Bank. Imagine a future where accessing and understanding complex datasets is as easy as asking a question. With Project StatGPT, that future is now. We're on a mission to democratize data access through the power of Large Language Models (LLMs) based on Natural Language Processing (NLP). StatGPT is designed to bridge the gap between vast data repositories and the business people who need insights from them, using intuitive, conversational interfaces.

We welcome DevOps engineers to help us in keeping up delivering superior services to our clients. We expect our DevOps engineers to have the following scope of responsibilities. Here we provide a list of skills and technologies we are interested in. See for yourself, whether any of them are in your scope of expertise or interest. You do not have to master all of them. Tell us what your strong side is and we will find the right task for you. We value the thrive for knowledge and self-development within our team

Responsibilities

Automation of continuous integration and continuous delivery for multiple customized installations
Management and utilization of cloud providers (AWS/Azure/GCP)
Operational infrastructure maintenance (monitoring, logs, and alerts)
Work in close cooperation with the R&D and the Support teams

Requirements

Fluent with Kubernetes and Docker
Strong experience in main cloud providers (AWS, GCP, Azure)
Production experience with cloud services: Kubernetes, Domain Management, Load Balancer, DB technologies, and CDN services (Cloudflare)
Being familiar with infrastructure as code approach, helm charts
Experience in installing/configuring/working with monitoring systems (Application insights, DataDog, Grafana or other similar) and logs systems (ELK, logz.io or other similar)
Knowledge of Github and Gitlab CI/CD, Github Actions
Experience in Security domain will be considered as a strong advantage