Lead Instructor, QA Automation & SDET Engineering

About Edversity

Edversity is a technology learning platform based at the National Science & Technology Park, NUST, Islamabad. We have trained more than 12,000 learners through live programs in Artificial Intelligence, Cybersecurity, Cloud, Blockchain, Data, and emerging technologies.
We are launching our QA Automation & SDET Engineering Program, a modern, AI-powered specialization designed to prepare learners for careers in software quality engineering, test automation, SDET, and AI quality engineering.
We are looking for an experienced industry practitioner to lead the program.

Who We Are Looking For

We are not looking for someone who has only taught software testing or completed certifications.
We are looking for a practitioner who has built automation frameworks, debugged failing pipelines, worked with engineering teams, reviewed test code, and understands what good quality engineering looks like in production.
The right instructor should be able to help a student move from:
Junior SQA / Associate QA → QA Automation Engineer → SDET → Quality Engineer → AI Quality Engineer

The Role

You will lead a 12-week, 72-hour live program designed to prepare learners for roles including:

• QA Automation Engineer
• Software Development Engineer in Test (SDET)
• Software Test Engineer
• Quality Engineer
• API Test Engineer
• AI Quality Engineer

This is a highly practical teaching role.
You will deliver live technical sessions, review automation frameworks and student code, mentor capstone projects, conduct technical clinics, and help assess students for internships and employer referrals.
The role is designed to run alongside a full-time engineering position.

Key Responsibilities

• Deliver three live technical sessions each week
• Teach through live coding, demonstrations, debugging, and practical engineering exercises
• Guide students in building production-style test automation frameworks
• Review student code, GitHub repositories, pull requests, and technical assignments
• Conduct framework reviews and technical defence sessions
• Mentor students on automation, API testing, CI/CD, and quality engineering practices
• Guide students through the development of their final SDET capstone
• Help students identify and resolve flaky tests, automation failures, and framework-design issues
• Demonstrate how modern QA teams use AI coding assistants and agentic testing tools
• Introduce students to testing and evaluating AI-powered applications
• Conduct technical interview preparation and review take-home assignments
• Keep program content aligned with current software-testing and quality-engineering practices
• Identify high-performing graduates suitable for internships and employer referrals
• Collaborate with Edversity's teaching assistants, cohort team, and industry reviewers

Program Areas

The program covers:

Quality Engineering Foundations

• Software Development Life Cycle and Agile workflows
• Test planning and risk-based testing
• Test-case design
• Exploratory testing
• Professional bug reporting
• Jira and GitHub workflows

Programming for Test Automation

• JavaScript and TypeScript
• Async programming
• Object-oriented programming
• Test utilities and configuration
• Git and GitHub
• Basic Python exposure

Web Test Automation

• Playwright
• Page Object Model
• Fixtures and authentication reuse
• Data-driven testing
• Cross-browser testing
• Network mocking
• Parallel execution and sharding
• Visual regression
• Accessibility testing
• Debugging and flaky-test engineering

Automation Frameworks

• Framework architecture and maintainability
• Playwright as the primary automation framework
• Selenium and Cypress literacy
• Allure and automated reporting

API and Database Testing

• REST API testing
• Postman and Newman
• Playwright API testing
• Authentication and authorization testing
• Schema validation
• SQL and database assertions
• Data setup and teardown
• Contract-testing concepts

DevOps for Quality Engineering

• Docker
• GitHub Actions
• CI/CD pipelines
• Automated PR quality gates
• Test reporting
• Environment management
• Secrets management
• Jenkins and GitLab CI concepts

Performance and Mobile Testing

• k6 performance testing
• Load, stress, and spike testing
• Appium fundamentals
• Mobile automation concepts
• JMeter literacy

AI-Powered Test Engineering

• GitHub Copilot, Claude Code, ChatGPT, and similar AI coding assistants
• AI-assisted test generation
• AI-assisted debugging and failure analysis
• Synthetic test-data generation
• Agentic testing workflows
• Playwright MCP and Test Agents
• Reviewing and validating AI-generated automation code

Testing AI Systems

• LLM application testing
• AI evaluation methodologies
• Golden datasets and evaluation rubrics
• Hallucination and faithfulness testing
• RAG evaluation
• LLM-as-a-judge techniques
• Promptfoo
• DeepEval
• Ragas
• Prompt injection and AI security testing
• AI red teaming
• Regression testing for AI applications
• Quality gates for AI systems

Requirements

• Five or more years of professional experience in QA automation, SDET, software testing, or quality engineering
• Strong hands-on experience building and maintaining automated testing frameworks in production environments
• Practical experience with Playwright and/or Selenium
• Strong programming skills in JavaScript or TypeScript
• Experience with API testing and tools such as Postman
• Strong understanding of Git and modern software-development workflows
• Practical experience integrating automated testing into CI/CD pipelines
• Experience with GitHub Actions, Jenkins, GitLab CI, or equivalent CI/CD platforms
• Working knowledge of Docker and test-environment management
• Experience diagnosing flaky tests, failed automation pipelines, and production-quality issues
• Understanding of test architecture, framework design, and maintainable automation practices
• Regular use of AI coding assistants such as GitHub Copilot, Claude Code, ChatGPT, Cursor, or similar tools
• Strong communication and mentoring skills
• Ability to explain engineering concepts through practical examples rather than only theory
• Strong communication skills in English and Urdu
• Availability for fixed evening sessions for 12 consecutive weeks

Preferred Experience

Experience in any of the following would be an advantage:

• Playwright framework ownership
• API automation
• Performance testing using k6 or JMeter
• Mobile automation using Appium
• SQL and database validation
• Test reporting using Allure
• AI-assisted software testing
• Testing LLM or RAG-based applications
• Promptfoo, DeepEval, Ragas, LangSmith, or similar AI evaluation tools
• Technical interviewing or mentoring junior QA engineers
• Experience working at a software product company or engineering-led technology organization

Previous teaching experience, postgraduate qualifications, and vendor certifications are not required.
We are primarily looking for a strong practitioner who can teach from real engineering experience.

Time Commitment

Approximately 10 to 14 hours per week, including:

• 6 hours of live instruction
• Session preparation
• Student code and assignment reviews
• Technical clinics and framework reviews
• Capstone mentoring
• Limited student support outside class

The program runs for 12 consecutive weeks.
You will be supported by:

• Teaching assistants
• A full-time cohort manager
• Practitioner reviewers
• An AI Quality Engineering guest instructor where required
• Edversity's placement and employer-relations team

What We Offer

• Competitive per-cohort compensation
• Ownership of technical program delivery
• Public visibility as the program's Lead Instructor
• Opportunity to shape one of Edversity's flagship engineering programs
• Access to Edversity's employer and technology ecosystem
• Support from teaching assistants and cohort operations
• Opportunities to lead future cohorts
• Opportunities to participate in employer sessions, Demo Days, and industry events
• A teaching schedule designed to work alongside a full-time engineering role