Position: DevOps engineer at Marketing platform
Company: Xenoss
Experience required: 3y
Category: DevOps
English level: upper
Published: 2022-03-01T00:00:00+02:00

Required skills

— At least 3 years of experience in a team environment
— Good knowledge of Linux
— Proficiency with Docker & Kubernetes
— Creating and maintaining fully automated CI/CD pipelines for code deployment
— Managing cloud infrastructure on AWS (EC2, S3) including backups and scaling
— Experience with DB management
— Knowledge of Git
— Working proficiency in English

— Do not hesitate to apply if you are missing some specific experience. We will be happy to help you with gaining one.

As a plus

— Terraform/Ansible
— Gitlab CI/CD
— DB sharding
— RabbitMQ

We offer

— Teams of people who love programming
— Complex technical challenges with big data/AI/high load
— Freedom to make your own engineering decisions and broad space for creativity
— Modern technology stack to work with
— Work remotely or from the office options on a flexible schedule
— Long-lasting projects
— Financial compensation for professional events and education
— Opportunity to choose the equipment you like
— Above-market compensation

Responsibilities

— You’ll be working in a DevOps team (you + another DevOps engineer)
— You’ll be defining and maintaining development environment automation for the team of developers (setting up CD/CI, configurations and deployment automation), maintaining test and production environment
— You’ll be communicating with users, developers & QAs on a daily basis to ensure smooth operations.

Project description

Client: Successful British ad-tech company with big global clients including Virgin, Nestle, Adidas, J&J, Uber, Nissan, Shell, HSBC.

Project: The product we are building is an AI-powered SaaS platform for managing marketing campaigns and generating promotional visuals (mainly digital ads), that is used by global top brands.

The solution helps big global brands to automate the creation of marketing creatives with help of AI/ML, configure advertising campaigns in buying platforms (Google, Facebook and more), analyze performance data and discover insights, optimize performance, grow revenue & increase customer satisfaction. Through AI, creative can be reformatted at speed and scale, and automatically edited to suit the location and audience it is intended for, saving production costs and ensuring relevance.

Building technology for smart advertising solutions is one of the biggest modern challenges that currently exist. Making ads to be more efficient, more relevant & less intrusive will benefit both advertisers and users. By collecting and analyzing (big) data on user reaction to the creatives, the platform learns & provides the most relevant creatives for each user segment (audience).

Tech stack: Node.js, Express.js, React.js, Redux, Rematch, Typescript, Python, Java, RabbitMQ, MongoDB, ClickHouse OLAP DBMS, Redis (cache), Elasticsearch, AWS, Docker, Kubernetes