Quality Intelligence (QI) Consultant
Experience: 12+ Years
Role Type: Full Time
Position Overview
We are looking for an experienced Quality Intelligence (QI) Consultant to lead enterprise-scale Quality Engineering transformation initiatives. This role combines AI-powered Quality Intelligence, enterprise test automation, quality analytics, and continuous testing to help organizations modernize their Quality Engineering capabilities.
The ideal candidate will bring strong technical expertise in automation architecture along with the consulting and leadership skills required to assess existing QE environments, define transformation roadmaps, implement AI-enabled testing capabilities, and improve release quality and delivery speed.
Key Responsibilities
Define enterprise Quality Intelligence strategies, operating models, transformation roadmaps, and governance frameworks.
Assess existing testing processes, automation frameworks, tools, environments, quality metrics, and release practices.
Lead AI-enabled Quality Engineering initiatives including:
AI-assisted test generation
Intelligent test optimization and risk-based testing
Self-healing automation
Defect prediction and predictive quality analytics
Test impact analysis
Synthetic test data generation
AI-assisted test maintenance
Architect and modernize enterprise automation frameworks across Web, API, Mobile, Desktop, and enterprise applications.
Drive modernization from fragmented or commercial automation solutions toward scalable, reusable, and open-source automation ecosystems.
Integrate automated testing with DevOps and CI/CD pipelines to enable continuous testing and automated quality gates.
Establish Quality Intelligence dashboards, KPIs, quality observability, predictive analytics, and executive-level reporting.
Conduct transformation workshops and provide consulting, coaching, and technical guidance to Quality Engineering teams.
Partner with business, product, engineering, QA, and leadership teams to improve release confidence and overall engineering quality.
Lead and mentor globally distributed Quality Engineering teams.
Required Skills & Experience
12+ years of experience in Quality Engineering, Test Automation, Software Quality, or Quality Transformation.
At least 5 years of experience leading enterprise automation architecture, quality modernization, or continuous testing initiatives.
Strong expertise in enterprise Test Automation Architecture and Quality Engineering transformation.
Hands-on experience with modern automation technologies such as Playwright, Selenium, Cypress, Appium, REST Assured, or similar tools.
Experience designing automation solutions across Web, API, Mobile, and enterprise applications.
Strong understanding of CI/CD, Continuous Testing, DevOps/DevSecOps, automated quality gates, and Agile delivery.
Experience with platforms and technologies such as Azure DevOps, Jenkins, Docker, Kubernetes, and major cloud platforms.
Experience implementing or working with AI-enabled Quality Engineering capabilities.
Strong understanding of quality metrics, analytics, governance, and automation modernization.
Excellent consulting, stakeholder management, communication, and problem-solving skills.
AI & Quality Intelligence Experience
Experience in one or more of the following areas is highly valuable:
Generative AI / LLMs for Quality Engineering
AI-assisted test generation
Intelligent/risk-based test selection
Predictive defect analytics
Self-healing automation
AI-assisted automation maintenance
Test impact analysis
Synthetic test data
Agentic AI
Quality Engineering for AI/ML applications
Responsible AI frameworks
Preferred Experience
Experience within Banking & Financial Services, Insurance, Retail & E-commerce, Healthcare & Life Sciences, Manufacturing, or Telecommunications.
Cloud experience across AWS, Azure, or GCP.
Relevant certifications in Quality Engineering, Test Automation, Agile, Cloud, or AI/Generative AI.
Certifications such as ISTQB Advanced Test Automation Engineer, Certified Agile Tester, or relevant automation/cloud certifications are advantageous.
Key Competencies
Quality Intelligence Strategy | Enterprise Test Automation Architecture | AI-Driven Quality Engineering | Automation Modernization | Continuous Testing | Quality Analytics | Shift-Left & Shift-Right Testing | DevSecOps Integration | Test Automation Governance | Quality Transformation
:::