AI Automation Engineer (Browser Automation + AI Tooling)
About QualMinds:
QualMinds is a global technology company dedicated to empowering clients on their digital transformation journey. We help our clients to design & develop world-class digital products, custom software and platforms. Our primary focus is delivering enterprise grade interactive software applications across web, desktop, mobile, and embedded platforms.
Position Summary:
We are seeking an AI Automation Engineer to help design and build intelligent automation systems using modern AI tooling and browser automation frameworks such as Stagehand and Playwright. This role focuses on developing automation workflows for testing, quality assurance, monitoring, and operational efficiency across web platforms and digital products. The ideal candidate has strong automation fundamentals and is excited to work with emerging AI-driven automation approaches.
Key Responsibilities - Automation Development
Build and maintain automation workflows using AI-assisted tooling (Stagehand or similar)
Develop browser automation suites using Playwright
Contribute to prompt-driven automation and agent workflows
Support development of reusable automation utilities and frameworks
Key Responsibilities - QA and Platform Automation
Build automated tests for UI, APIs, and data workflows
Support regression and functional automation suites
Help automate monitoring and validation workflows
Integrate automation into CI/CD pipelines
Key Responsibilities - AI / LLM Integration
Assist in integrating LLM APIs into automation workflows
Contribute to prompt design and evaluation workflows
Help implement guardrails and validation checks
Support performance and cost optimization of AI usage
Key Responsibilities - Observability and Reporting
Help build automation reporting dashboards
Instrument automation with logging and metrics
Support troubleshooting automation failures
Key Responsibilities - Engineering Judgment & AI Usage
Understand when to use traditional deterministic automation vs. AI-driven approaches
Recognize scenarios where AI introduces unnecessary complexity or cost
Implement stable, selector-based automation for predictable UI patterns
Reserve AI for truly dynamic or unpredictable scenarios
Balance automation speed, cost, and reliability when choosing implementation approaches
Document automation decisions and trade-offs
Required Qualifications - Engineering Fundamentals
2–5 years of software engineering, QA automation, or automation engineering experience
Python (required)
TypeScript / JavaScript (preferred for some roles)
Experience with async/await patterns and concurrent programming
Required Qualifications - Automation Experience
Hands-on experience with Playwright or similar browser automation frameworks
Experience automating web application workflows
Ability to write robust CSS selectors and XPath expressions
Experience working with dynamic content and asynchronous page loading patterns
Understanding of when to use deterministic vs. probabilistic automation
Required Qualifications - AI and Modern Tooling Exposure
Exposure to LLMs, AI APIs, or AI automation tooling
Basic understanding of prompt engineering concepts
Ability to recognize when AI should NOT be used: - Stable, predictable UI patterns (use traditional selectors) - Performance-critical paths (AI adds latency) - Cost-sensitive operations (AI calls have API costs) - Scenarios requiring deterministic behavior (compliance, legal)
Understanding of automation cost/benefit trade-offs
Experience balancing speed, reliability, and maintainability
Required Qualifications - DevOps and Platform Fundamentals
Experience working with CI/CD pipelines
Familiarity with containerized or cloud-hosted environments
Familiarity with SQL databases (MySQL, PostgreSQL, etc.)
Preferred Qualifications
Exposure to Stagehand or similar AI agent automation frameworks
Experience working on SaaS or multi-tenant web platforms
Experience with API automation or integration testing
Exposure to observability or monitoring tools
Experience working in production web environments
Experience with email processing, PDF generation, or document workflows
Experience with Salesforce APIs or other CRM integrations
Knowledge of distributed task queues (Celery, RabbitMQ, Redis)
Experience with Kubernetes or container orchestration
Understanding of pytest or similar Python testing frameworks
Experience with observability tools (Sentry, Datadog, etc.)
Success Metrics (First 6–12 Months)
Contribute to production automation workflows
Reduce manual testing through expanded automation coverage
Improve automation reliability and reporting
Help build reusable automation components and patterns
Work Environment
Collaborative engineering and product teams • Modern cloud and automation tooling
Opportunity to work directly with emerging AI technologies
Fast-paced, innovation-focused environment
