Automation Tester (AI Coach)

We provide complete software development teams, who will take complex care of your software. We are experienced in building teams uniquely suited to the specific needs of our clients. One team - a range of skills, diverse personalities, and various approaches.

• 5–8 years of experience as an Automation Tester or in related software quality assurance roles
• Very good knowledge of testing and CI/CD tools such as Selenium, Jenkins, Postman, GitHub, Bitbucket, Kibana, JMeter, and SQL
• Practical experience using AI tools supporting IT teams, including GitHub Copilot, Microsoft 365 Copilot, ChatGPT, Claude, or Ollama
• Good knowledge of IT environments and software development processes in large organizations, especially in the financial and banking sectors
• Highly developed communication skills with the ability to effectively transfer knowledge and support others' development
• Ability to simplify complex technical issues and present them understandably to various audiences
• Knowledge of the modern AI ecosystem, including LLM, generative AI, process automation, and productivity tools
• Ability to design effective prompts, workflows, and AI usage scenarios for daily IT team work
• Process-oriented and analytical approach to identifying areas where AI implementation can bring measurable business value

• Designing and conducting training, workshops, and consultation sessions to support effective use of AI tools by testers and development teams
• Supporting users in creating effective prompts and implementing best practices for working with generative AI
• Creating and developing an internal knowledge base covering standards, recommendations, and proven methods for using AI in software development and testing processes
• Monitoring technological trends and new AI solutions, actively sharing knowledge and recommendations within the organization
• Analyzing and comparing AI solutions (e.g., GitHub Copilot, Microsoft 365 Copilot, and alternative tools) regarding quality, cost, security, risk, and compliance with organizational requirements
• Defining, monitoring, and reporting KPIs/OKRs and ROI for AI initiatives, focusing on productivity, solution quality, and cost optimization
• Coordinating AI adoption initiatives, collaborating with business and technical stakeholders, and supporting organizational transformation towards effective AI use