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• Test web and mobile applications using all available methods (including automated regression suites, API validation, and exploratory testing of the app) • Perform risk-based exploratory testing to identify critical defects beyond scripted checks, ensuring testing efforts are prioritized where they matter most. • Design, maintain, and improve automated test scripts in Playwright and Python. • Analyze the product and its business and technical requirements to design high-value test scenarios and scripts that form the foundation for robust automation. • Perform API testing with Postman, including automated API test execution. • Collaborate with developers and product teams in an Agile/Scrum environment. • Support CI/CD testing processes (GitLab CI). • Report and track defects using Jira and document findings in Confluence. • Participate in the adoption and daily use of AI testing tools (e.g., for test creation and defect analysis). • Contribute to improving QA processes and share knowledge with the team.

• Support the development of industry-leading software products • Work within an international Scrum team • Act as the key interface between Product, Engineering, UX/UI, and Business stakeholders • Collaborate with cross-functional teams to define and implement data-driven solutions • Analyze and optimize business processes and product functionalities • Elicit, structure, and validate business requirements • Translate business needs into detailed functional specifications and system models (UML/BPMN) • Define acceptance criteria and support QA processes • Conduct profitability and risk analysis based on KPIs and business metrics

• Design, develop, and maintain backend services and platform components in Go for our AI platform • Rapidly iterate and deliver new features supporting AI-driven products and internal tools • Build scalable, reliable backend services in Go • Design and implement APIs and integrations between services and external systems • Define and design AI solution architectures and lead their implementation together with the engineering team • Build and orchestrate AI agents and agentic workflows using LLM models and external tools • Contribute architectural ideas and propose pragmatic technical solutions • Design systems with clear failure modes and debuggability in mind • Actively participate in code reviews to maintain high engineering standards • Collaborate closely with the Product Owner to deliver features from concept to production • Stay up-to-date with the latest developments in AI and integrate emerging technologies when they provide real value • Support development of frontend applications where needed, in collaboration with the wider team

• Collaborate closely with architects, developers, QA, and security teams to ensure smooth and reliable environment operations • Work in close partnership with the platform team, based on shared ownership, knowledge exchange, and mutual support • Own and operate containerized application platforms based on Docker and Kubernetes, ensuring reliability, scalability, and operational excellence • Design and deliver dynamic test environments at scale, including multiple parallel, per–merge request (branch-based) deployments • Build, maintain, and standardize CI/CD pipelines by creating reusable templates and components in GitLab CI • Drive deployment automation and GitOps practices • Identify operational bottlenecks and implement automation to reduce manual effort and improve delivery speed • Embed security-by-design across the SDLC, including pipeline hardening and automated security checks • Build and operate observability platforms: monitoring, logging, and diagnostics (Prometheus, Grafana, ELK/EFK/Loki, etc.) • Participate in on-call and incident response, including troubleshooting, root-cause analysis, and post-mortems • Take end-to-end ownership of the solutions you build (“you build it, you run it”).

• Collaborate closely with architects, developers, QA, and security teams to ensure smooth and reliable environment operations • Work in close partnership with the platform team, based on shared ownership, knowledge exchange, and mutual support • Own and operate containerized application platforms based on Docker and Kubernetes, ensuring reliability, scalability, and operational excellence • Design and deliver dynamic test environments at scale, including multiple parallel, per–merge request (branch-based) deployments • Build, maintain, and standardize CI/CD pipelines by creating reusable templates and components in GitLab CI • Drive deployment automation and GitOps practices • Identify operational bottlenecks and implement automation to reduce manual effort and improve delivery speed • Embed security-by-design across the SDLC, including pipeline hardening and automated security checks • Build and operate observability platforms: monitoring, logging, and diagnostics (Prometheus, Grafana, ELK/EFK/Loki, etc.) • Participate in on-call and incident response, including troubleshooting, root-cause analysis, and post-mortems • Take end-to-end ownership of the solutions you build (“you build it, you run it”).

• Help ensure the quality and reliability of products used by thousands of users • Be introduced to the fundamentals of software testing • Learn to work with web and mobile applications • Get hands-on practice with test automation and programming • Collaborate with team members and receive mentorship, training, and guidance to build strong foundations in QA and software development

• Design, develop, and maintain full-stack applications (Go + React) for our AI platform. • Rapidly iterate and deliver new functionality supporting AI-driven products and internal tools. • Build scalable and reliable backend services in Go. • Develop and maintain frontend applications using React. • Design and implement APIs and integrations between services and external systems. • Define and design AI solution architectures and drive their implementation together with the engineering team. • Build and orchestrate AI agents and agentic workflows using LLM models and external tools. • Contribute architectural ideas and propose pragmatic technical solutions. • Design systems with clear failure modes and debuggability in mind. • Actively participate in code reviews to maintain high engineering standards. • Collaborate closely with Product Owner to deliver features from concept to production. • Stay up-to-date with the latest developments in AI and integrate emerging technologies when they provide real value.

• Maintain and enhance existing PHP-based applications • Analyze and work with legacy codebases and system architecture • Identify, troubleshoot, and fix bugs and performance issues • Refactor legacy code to improve readability, stability, and maintainability • Implement new features within existing system constraints • Support gradual modernization of outdated components • Write clean, structured code aligned with OOP and Clean Code practices • Collaborate with QA, DevOps, and Product teams to ensure stable releases • Write and maintain automated tests where feasible • Contribute to technical documentation • Participate in code reviews and technical discussions

• Validate requirements in collaboration with product owners. • Analyze source code and data structures. • Translate business needs into domain models. • Support engineering teams during implementation.