
1001 - 5000 employees
Founded 2002
đź Gaming
đĄ Telecommunications
Software Development âą Gaming âą Telecommunications
Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.
đ May 28
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1001 - 5000 employees
Founded 2002
đź Gaming
đĄ Telecommunications
Software Development âą Gaming âą Telecommunications
Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.
âą Define and evolve the engagement model for AI-native test automation initiatives âą Adapt and extend the universal rule and skill system for different client environments âą Advise senior stakeholders on quality strategy, SDLC improvements, automation maturity, and AI adoption âą Drive framework standardization while balancing project-specific requirements âą Review AI-generated outputs, including code, architecture decisions, reports, rules, and testing artifacts âą Quickly identify systemic issues, false positives, broken contracts, redundant logic, or inefficient implementations âą Trace issues to their root causes and define corrective actions at the right system layer âą Improve the reliability and quality of AI-assisted engineering workflows âą Define principles and guardrails for effective AI usage in test automation âą Work with AI coding agents and structured prompting approaches to optimize engineering workflows âą Continuously improve prompts, skills, layered rules, and framework integrations âą Optimize token usage and cost efficiency while maintaining delivery quality âą Own and evolve a scalable Playwright + TypeScript automation framework âą Design and maintain page objects, reusable page-element components, fixtures, selectors, reporting, and test data management âą Establish and enforce strong test-design standards and architectural consistency âą Support portability and scalability of the framework across multiple engagements
âą Strong hands-on experience with Playwright and TypeScript test automation architecture âą Proven experience building and evolving automation frameworks from scratch âą Deep understanding of scalable E2E testing design patterns and framework organization âą Experience working with AI coding agents such as Cursor, Claude Code, or similar tools âą Strong analytical skills with the ability to validate and challenge AI-generated outputs âą Experience defining methodologies, playbooks, standards, or reusable engineering practices âą Excellent communication and stakeholder management skills âą Ability to work in customer-facing advisory and consulting environments âą Upper-Intermediate level of English âą WILL BE A PLUS: Experience building AI-native QA or engineering workflows âą Knowledge of token optimization and AI operational economics âą Experience leading or scaling QA/automation practices âą Understanding of SDLC transformation and quality engineering strategy âą Experience working in consulting or multi-client delivery environments
âą Employees can work remotely
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