Test Automation Engineering·Confirmed live in the last 24 hours·
Full-timeKarachi, Karachi City, Sindh, PakistanIn-person
About the Job
Requirements
A bachelor's degree in Computer Science, Engineering, or a related field.
At least 6 years of software quality assurance experience, including strong hands-on automation experience.
Proven expertise with Selenium and Python, with strong practical programming and debugging ability.
Strong knowledge of Python, Java, or JavaScript and the ability to write clean, maintainable, production-quality automation code.
Strong understanding of automation framework architecture, test design, assertions, synchronization, test data management, and maintainability.
Experience integrating automated tests with CI/CD pipelines such as Jenkins or GitLab CI.
A solid understanding of API testing and automation using tools such as Postman, REST Assured, or equivalent frameworks.
A strong understanding of functional, regression, integration, end-to-end, and backend testing.
Experience working with Git and modern source-control workflows.
A strong understanding of Agile/Scrum methodologies and experience working closely with development and product teams.
Practical experience using AI/LLM tools in software testing or software engineering workflows, including test generation, automation assistance, debugging, documentation, or test analysis.
Understanding of prompt engineering and the ability to critically review, validate, and improve AI-generated test cases or automation code rather than relying on AI output without verification.
Awareness of AI-assisted testing approaches such as intelligent test generation, self-healing automation, visual testing, test-impact analysis, and AI-assisted failure triage.
Strong problem-solving, analytical, debugging, and root-cause-analysis skills with attention to detail.
Effective communication and collaboration skills, including the ability to mentor junior QA engineers and work with cross-functional teams.
Responsibilities
Drive QA best practices and continuously improve testing methodologies, coverage, reliability, and execution efficiency.
Perform hands-on automation testing across UI, API, and backend/service layers to provide comprehensive, risk-based test coverage.
Design, develop, refactor, and maintain scalable, reusable, stable, and maintainable automation frameworks and test suites.
Apply sound automation architecture and coding practices, including SOLID principles, Page Object and other appropriate design patterns, reusable utilities, data-driven testing, proper assertions, logging, and robust synchronization.
Integrate automated tests into CI/CD pipelines such as Jenkins or GitLab CI and establish reliable quality gates and reporting.
Collaborate with product managers, developers, business stakeholders, and other QA engineers to understand requirements, identify risks, and define effective automation strategies.
Create and maintain test cases and automated coverage for functional, regression, integration, API, and end-to-end scenarios.
Investigate automation failures, distinguish application defects from test or environment issues, and perform root-cause analysis.
Contribute to performance testing and support a broader quality strategy covering functional, performance, security, and reliability considerations.
Mentor and coach junior QA engineers on automation practices, framework usage, debugging, coding standards, and test design.
Use AI/LLM-based tools to accelerate test-case generation, test-data creation, code generation and refactoring, failure analysis, documentation, and repetitive QA activities, while independently reviewing and validating AI-generated outputs.
Apply prompt-engineering techniques to produce useful, consistent, and context-aware test scenarios, automation code, and QA documentation.
Evaluate and adopt suitable AI-assisted testing capabilities, including intelligent test generation, visual validation, test-impact analysis, failure triage, and self-healing automation where they provide measurable value.
Identify opportunities to use AI agents or MCP/tool-integrated workflows to improve test execution, defect investigation, reporting, and QA productivity while following organizational security and data-handling requirements.
Ensure AI-assisted QA activities do not compromise confidential data, credentials, customer information, source code, or other restricted information.
Operate effectively within an Agile/Scrum environment and align QA activities with sprint goals, release timelines, and Definition of Done.
Desired Qualifications
Performance testing experience is highly desirable.
Experience with Playwright or Cypress in addition to Selenium.
Experience with cloud-based test execution and/or AWS or Azure.
Experience with Docker, containerized test execution, or parallel/distributed testing.
Experience with performance testing tools such as JMeter or equivalent.
Experience with AI coding/testing assistants, LLM APIs, agentic QA workflows, or MCP/tool-integrated automation workflows.
Experience building or maintaining automation frameworks used by multiple teams or across multiple applications.
ISTQB Certification or other relevant certifications.
Overview: Enterprise64 is a U.S.-based technology company that creates digital solutions for startups to Fortune 500 companies in the United States, Europe, and the United Arab Emirates. We are growing rapidly across all our global offices and have career opportunities for individuals who are looking to work in a fast-growing company, work in a friendly environment, looking to be challenged, grow, and fast-track their careers.
Job Description: Enterprise64 is seeking an experienced QA Automation Engineer specializing in Selenium with hands-on Python expertise. The successful candidate will design, develop, maintain, and evolve scalable automation solutions across UI, API, and backend layers. The role requires strong knowledge of software testing principles, automation architecture, CI/CD, Agile methodologies, and coding best practices such as clean code, reusable components, proper assertions, and SOLID principles. As part of our AI-forward engineering culture, the engineer will champion the adoption of AI-assisted testing tools and methodologies to accelerate test automation, enhance test coverage and software quality, improve QA efficiency, and drive innovation across the software development lifecycle.
Responsibilities:
6+ years in automation tools and frameworks, responsible for driving QA best practices and continuously improving testing methodologies, coverage, reliability, and execution efficiency.
Perform hands-on automation testing across UI, API, and backend/service layers to provide comprehensive and risk-based test coverage.
Design, develop, refactor, and maintain scalable, reusable, stable, and maintainable automation frameworks and test suites.
Apply sound automation architecture and coding practices, including SOLID principles, Page Object/appropriate design patterns, reusable utilities, data-driven testing, proper assertions, logging, and robust synchronization.
Integrate automated tests into CI/CD pipelines such as Jenkins or GitLab CI and establish reliable quality gates and reporting.
Collaborate with product managers, developers, business stakeholders, and other QA engineers to understand requirements, identify risks, and define effective automation strategies.
Create and maintain test cases and automated coverage for functional, regression, integration, API, and end-to-end scenarios.
Investigate automation failures, distinguish application defects from test/environment issues, and perform root-cause analysis.
Contribute to performance testing and support a broader quality strategy covering functional, performance, security, and reliability considerations.
Mentor and coach junior QA engineers on automation practices, framework usage, debugging, coding standards, and test design.
Use AI/LLM-based tools to accelerate test-case generation, test-data creation, code generation/refactoring, failure analysis, documentation, and repetitive QA activities, while independently reviewing and validating AI-generated outputs.
Apply prompt-engineering techniques to produce useful, consistent, and context-aware test scenarios, automation code, and QA documentation.
Evaluate and adopt suitable AI-assisted testing capabilities, including intelligent test generation, visual validation, test-impact analysis, failure triage, and self-healing automation where they provide measurable value.
Identify opportunities to use AI agents or MCP/tool-integrated workflows to improve test execution, defect investigation, reporting, and QA productivity while following organizational security and data-handling requirements.
Ensure AI-assisted QA activities do not compromise confidential data, credentials, customer information, source code, or other restricted information.
Operate effectively within an Agile/Scrum environment and ensure QA activities align with sprint goals, release timelines, and Definition of Done.
Requirements:
Bachelor’s degree in Computer Science, Engineering, or a related field.
6+ years of software quality assurance experience, with strong hands-on experience in automation.
Proven expertise with Selenium and Python; strong practical programming and debugging ability.
Strong knowledge of Python, Java, or JavaScript and ability to write clean, maintainable, production-quality automation code.
Strong understanding of automation framework architecture, test design, assertions, synchronization, test data management, and maintainability.
Experience integrating automated tests with CI/CD pipelines such as Jenkins or GitLab CI.
Solid understanding of API testing and automation using tools such as Postman, REST Assured, or equivalent frameworks.
Strong understanding of functional, regression, integration, end-to-end, and backend testing; performance testing experience is highly desirable.
Experience working with Git and modern source-control workflows.
Strong understanding of Agile/Scrum methodologies and experience working closely with development and product teams.
Practical experience using AI/LLM tools in software testing or software engineering workflows, including test generation, automation assistance, debugging, documentation, or test analysis.
Understanding of prompt engineering and the ability to critically review, validate, and improve AI-generated test cases or automation code rather than relying on AI output without verification.
Awareness of AI-assisted testing approaches such as intelligent test generation, self-healing automation, visual testing, test-impact analysis, and AI-assisted failure triage.
Experience with Playwright or Cypress in addition to Selenium.
Experience with cloud-based test execution and/or AWS or Azure.
Experience with Docker, containerized test execution, or parallel/distributed testing.
Experience with performance testing tools such as JMeter or equivalent.
Experience with AI coding/testing assistants, LLM APIs, agentic QA workflows, or MCP/tool-integrated automation workflows.
Experience building or maintaining automation frameworks used by multiple teams or across multiple applications.
ISTQB Certification or any other relevant certifications is a plus.
Strong problem-solving, analytical, debugging, and root-cause-analysis skills with attention to detail.
Effective communication and collaboration skills, with the ability to mentor junior QA engineers and work with cross-functional teams.