What you will do
- Have a high degree of autonomy and room for personal growth
- Build automation coverage on the project
- Organize knowledge sharing sessions and maintain project’s technical documentation
- Organize transition flow for QA team — from manual to automation QA
- At least 3 years of professional experience with backend automation
- At least 2 years of professional experience with UI automation
- A good understanding of software testing processes, techniques and the Software Development Life Cycle
- Experience with containerization and cloud technologies (eg. Kubernetes, Docker, AWS)
- Experience with tools (Github, Gitlab,SonarQube)
- Good spoken and written English (B1)
- Great troubleshooting and problem solving skills
- Experience working with MongoDB and Mongoose
- Deep experience with at least one mainstream messaging solution (RabbitMQ, SQS, NATS)
- Good understanding of container-based workflow, experience with Docker & Kubernetes
- Good estimation and time management skills.
- Experience with Jest, Supertest
- Experience with Cypress framework
- A desire to knowledge share and advocate for the use of modern technologies
- Experience with Clickhouse DB
What you get
- 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
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, RabbitMQ, MongoDB, ClickHouse OLAP DBMS, Redis (cache), Elasticsearch, AWS, Docker, Kubernetes