Description

We are developing a system that automates the entire lifecycle of an investment deal. Our teams work in the following areas:

• Algorithmic search for potential deals and clients

• Managing the process of concluding investment deals

• Financial calculations and portfolio valuation

• Building financial and management reporting for the Sber investment portfolio

• Investment services for our corporate clients.

We use the most modern technologies and are open to team member suggestions for changing the stack. You will work with a microservice architecture (Kubernetes, Docker, Istio, Kafka).

Responsibilities

• development and support of a unified automated testing system covering both the client side (UI) and the server side (API/DB)
• implementing the Shift Left practice: participating in sprint planning, assessing quality risks at the requirements analysis stage, proposing solutions to improve code testability.
• integrating automated tests into CI/CD pipelines (Jenkins, Kubernetes), ensuring fast feedback for the development team

Leading the AI direction in testing:

• researching and testing new AI tools for applicability in projects
• implementing successful solutions into workflows: from generating boilerplate code to intelligent defect analysis
• building a library of effective prompts and usage patterns for AI for the team
• if necessary, use Python or other languages to create utilities, scripts, or auxiliary testing tools.

Requirements

• minimum 4 years of experience in QA, with at least 2 years of intensive work in automation. (Java + Selenium/RestAssured)
• confident creation of automated tests for UI (Selenium) and API (RestAssured).
• Understanding of web application architecture, ability to work with databases (SQL, PgAdmin4 / DBeaver) to verify data integrity
• experience in introducing testing in the early stages of SDLC: participation in requirements and architecture reviews before development begins
• ability to configure automated test runs in CI/CD (Jenkins, Kubernetes, Git) as a mandatory gate before deployment
• willingness to help developers in writing Unit tests and increasing code coverage
• deep understanding of the capabilities of modern AI tools in the context of QA
• experience or willingness to initiate and implement AI solutions in testing processes: test data generation, auto-documentation, intelligent log analysis, risk prediction
• ability to compose precise and structured prompts for solving work tasks and transferring best practices to the team.

Conditions

• opportunity to choose a convenient work format: hybrid or office
• annual salary review, annual bonus
• corporate gym and recreation areas
• more than 400 educational programs from SberUniversity for professional and career development
• extended voluntary health insurance, preferential insurance for family and corporate pension program
• mortgage benefit of up to 7% for every employee
• free SberPrime+ subscription, discounts on products from partner companies
• referral bonus for recommending friends to join the Sber team.