Artificial Intelligence Engineer

Luxoft; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Luxoft seeks a GenAI UI Test Automation Engineer in the United States to accelerate UI automation and test generation using Python, Java and Selenium. You will customize and maintain AI Agents for testing, build reusable prompt libraries, and drive adoption of GenAI-powered testing practices across projects.

The role emphasizes hands-on development of AI-assisted testing tools, integration into testing workflows, and strong problem-solving and communication skills to collaborate with

Qualifications

• Hands-on experience with Generative AI tools such as Copilot, Claude, or similar
• Experience with agent workflows for test case generation and data generation
• Ability to create, customize, and maintain AI Agents for testing use cases
• Understanding of RAG concepts and vector-based retrieval
• Strong Python and Java programming skills
• Hands-on experience with Selenium WebDriver

Responsibilities

• Create reusable prompt libraries and AI-assisted testing accelerators.
• Analyze application behavior and identify opportunities to improve testing through GenAI solutions.
• Drive adoption of AI-assisted testing best practices across projects.
• Develop automated test scripts using Python (or Java).
• Design, develop, and maintain UI automation frameworks using Selenium.
• Leverage Generative AI tools and LLMs to improve testing efficiency and automation coverage.
• Integrate AI Agents into testing workflows for test case generation, script generation, execution analysis, and defect triaging.
• Collaborate with development and business teams to understand requirements and design automation solutions.
• Troubleshoot automation failures and enhance agent decision-making capabilities.

Skills

GenAI testing

Python

Java

Selenium

LLM tooling

Tools

Selenium WebDriver

GitHub Copilot

Claude

Job description

Job Description

Project Description:

We are seeking a highly skilled GenAI UI Test Automation Engineer with strong expertise in Python, Java, Selenium, and GenAI-powered testing solutions. The ideal candidate should have hands-on experience leveraging LLMs and open-source AI frameworks to accelerate UI automation, test generation, defect analysis, and testing productivity.

The candidate should be capable of customizing and maintaining AI Agents that support software testing activities, while demonstrating strong problem-solving, analytical, and communication skills.

Responsibilities:

• Create reusable prompt libraries and AI-assisted testing accelerators.
• Analyze application behaviour and identify opportunities to improve testing through GenAI solutions.
• Drive adoption of AI-assisted testing best practices across projects.
• Develop automated test scripts using Python (or Java).
• Design, develop, and maintain UI automation frameworks using Selenium.
• Leverage Generative AI tools and LLMs to improve testing efficiency and automation coverage.
• Integrate AI Agents into testing workflows for test case generation, script generation, execution analysis, and defect triaging.
• Collaborate with development and business teams to understand requirements and design automation solutions.
• Troubleshoot automation failures and enhance agent decision-making capabilities.

Mandatory Skills:

Artificial Intelligence (AI) Python

Mandatory Skills Description:

Hands-on experience with Generative AI tools such as Microsoft Copilot, GitHub Copilot, Claude, or similar

• Experience in working with agent workflows for:
• Test case generation
• Test data generation
• UI automation script generation
• Defect analysis
• Root cause analysis
• Test execution summarization
• Ability to create, customize, and maintain AI Agents for testing use cases.
• Understanding of RAG concepts and vector-based knowledge retrieval
• Strong hands-on experience with Selenium WebDriver.
• Strong Python Java programming skills.

Problem Solving & Communication

• Strong analytical and troubleshooting skills.
• Ability to solve complex testing challenges using AI-assisted approaches.
• Proven problem-solving capabilities and logical thinking.
• Strong verbal and written communication skills.
• Ability to articulate AI solutions and automation strategies to technical and non-technical stakeholders.