SDET (auto)

Automationanywhere; United States; Remote; USD 45,000 - 73,000; Full time

Job summary

Automation Anywhere ищет SDET с опытом в автоматизации и умением внедрять AI‑помощь в процесс тестирования. Вы будете развивать фреймворки, внедрять AI‑инструменты для генерации тестов и анализа дефектов, сотрудничать с командами разработки и продуктовым менеджером.

Требуется уверенное владение Java/Python/JavaScript, опыт с Playwright или Selenium и знакомство с TDD/BDD/ATDD. Ожидается активное участие в CI/CD workflow и обеспечении качества на всех этапах релиза.

Qualifications

• Бакалаврская степень в области компьютерных наук, компьютерной инженерии или смежной области.
• 2–5 лет опыта SDET или QA с опытом использования AI‑ассистированных инструментов тестирования.
• Глубокое понимание SDLC, STLC и современных методологий тестирования.

Responsibilities

• Разрабатывать и внедрять AI‑инструменты для тестирования и автономного создания тестов.
• Работать с Playwright или Selenium для UI и API тестирования.
• Интегрировать TDD/BDD/ATDD в CI/CD pipelines.
• Писать и поддерживать автоматизацию фронтенда и бэкенда, включая работу с AI‑генерируемым выводом.

Skills

Java

Python

JavaScript/TypeScript

AI‑assisted testing

CI/CD

Education

Bachelor's degree in Computer Science or related field

Tools

Playwright

Selenium

CI/CD tooling

Job description

Описание

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics— all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential. Our Opportunity: We are looking for a SDET who brings together deep automation expertise and a forward-looking AI-first mindset to redefine how quality is built into our products. You will lead the charge in adopting AI-powered testing tools, intelligent defect analysis, and autonomous test generation - while remaining the quality champion your team relies on. Location: Athens, Greece

Задачи: Director, Engineering Champion an AI-first testing culture by proactively identifying opportunities to integrate AI/ML-powered tools into test design, execution, maintenance, and defect analysis. Use AI-assisted tools to accelerate test authoring, improve coverage, and reduce the effort of maintaining test scripts. Leverage LLMs and AI assistants to generate test cases from requirements, user stories, and acceptance criteria, then validate, refine, and own the output. Apply AI-driven visual testing and self-healing automation techniques to reduce flakiness and keep test suites resilient through rapid UI changes. Implement AI-augmented log and anomaly analysis to identify patterns that precede failures in production or staging environments. Quickly build a deep understanding of the solution domain, analyze customer-reported defects, and implement automation strategies, powered by AI where applicable, to prevent recurrence. Act as the first customer of the product and its documentation, providing feedback from the customer’s perspective and serving as the quality champion for the team. Collaborate with product managers, developers, UX/UI designers, and fellow SDETs to understand functionality, identify test scenarios, and ensure comprehensive coverage. Review assigned backend and engineering stories, assess their impact, and define test coverage using an AI-assisted, risk-based approach. Perform functionality, integration, end-to-end, performance, and regression testing across all release phases, supported by AI-driven test selection and prioritization. Set up, maintain, and evolve test automation frameworks across Web, Desktop, and Mobile, incorporating AI capabilities for smarter execution and maintenance. Write and maintain automation code for front-end and back-end testing, including non-deterministic Agentic AI responses, using AI tools for debugging, refactoring, and coverage gap analysis. Build automation for customer use-case scenarios and customer-reported defects, using AI-generated scenario suggestions to expand coverage beyond manual thinking. Contribute actively to API/integration testing, UI automation, TDD, ATDD, and code quality tooling, using AI to boost throughput at every layer. Diagnose and resolve CI/CD pipeline issues and apply AI-based observability tools to detect and predict build instability. Perform database querying and log analysis for root cause investigation, using AI-assisted analysis where available to speed up triage. Share knowledge through workshops and learning sessions on AI tools, testing innovation, and SDET skill development. Continuously evaluate and introduce new AI-powered testing tools and methodologies, and advocate for their adoption across the team. Contribute to initiatives that improve team processes, tooling, and product quality, favoring intelligent automation over manual toil. Maintain clear documentation of test strategies, automation processes, and AI tooling decisions, so knowledge stays accessible and transferable.

Требования

Бакалаврская степень в области компьютерных наук, компьютерной инженерии или смежной области. 2-5 years of experience in SDET or quality engineering roles, with demonstrated exposure to AI-assisted testing or tooling. Strong understanding of the SDLC, STLC, and modern software testing methodologies. Proficiency in Java, Python, and/or JavaScript/TypeScript, with the ability to write, review, and debug automation code at scale. Hands-on experience with Playwright or Selenium for UI and API testing. Experience using LLMs or AI assistants (such as ChatGPT, Claude, or Copilot) to accelerate test authoring, code review, or defect analysis. Working knowledge of TDD, BDD, and ATDD, and integrating them into CI/CD pipelines. Experience with CI/CD pipelines, including triaging, stabilizing, and improving build and deployment workflows. Working knowledge of database querying and log/anomaly analysis, including AI-assisted observability platforms. Ability to critically evaluate AI-generated test output by validating, refining, and taking ownership of it. Problem-solving mindset, with the ability to debug complex issues in both handwritten and AI-generated automation code. Clear written and verbal communication with technical and non-technical stakeholders, including transparent documentation of AI tool decisions, and the judgment to ask for help when needed.