AI Strategic Consultant

Key Responsibilities:

• Lead end to end enterprise QE transformation by assessing current capabilities benchmarking maturity and defining AI first target state blueprints across people process and technology
• Design intelligent governance and operating models that embed predictive autonomous quality practices aligned to business outcomes while driving rapid value through early wins
• Enable sustainable change through executive alignment change management transition and knowledge transfer strategies and reduced dependency on consulting support
• Additionally support growth through C suite advisory pre sales leadership creation of proprietary IP and market shaping via thought leadership and industry engagement

Technical Requirements:

• Mandatory Skills
• These are essential for baseline success in an enterprise QE advisory leadership role
• 15 years of QE experience with enterprise scale transformation exposure
• Demonstrated ability to lead and advise large complex organisations
• QE strategy and operating model design
• Defining multi year QE roadmaps governance frameworks and risk based quality strategies
• Quality economics expertise
• Cost of quality analysis ROI articulation and tying QE outcomes to business metrics cost speed resilience
• Risk based and outcome driven QE leadership
• Driving measurable improvements in defect leakage release velocity reliability and compliance
• Modern engineering fluency at advisory level
• Strong understanding of DevOps CI CD cloud native and platform engineering concepts to translate technical complexity into actionable quality guidance without hands on pipeline work

Additional Responsibilities:

• Good to Have Skills
• These enhance differentiation and future proof the role but are not strictly required for core execution
• AI driven quality engineering advisory
• Guiding adoption of intelligent testing predictive risk analytics and autonomous quality capabilities
• AI risk assurance and trust frameworks
• Understanding AI model quality bias detection and data quality as QE expands into AI enabled products
• Advanced quality intelligence and analytics mindset
• Leveraging observability telemetry and production insights to influence testing and governance strategies
• Innovation and value realization focus
• Ability to distinguish genuine AI driven lift from vendor hype and steer clients toward pragmatic value outcomes

Preferred Skills:

Foundational ->Artificial Intelligence->Responsible AI by Design,Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->generative ai,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag),Technology->AI-Responsible AI->Responsible AI->explainable ai,Technology->API Testing->RestAssured,Technology->Architecture->Architecture - ALL,Technology->AI-Generative AI->Artificial Intelligence - BASIC,Technology->Automated Testing->Automated Testing - ALL,Technology->Automated Testing->Test automation framework design,Technology->Enterprise Architecture->Digital Architecture,Technology->Mobile Automation Testing->Mobile Test Automation process,Technology->Mobile Testing->BDD, TDD, ATDD for Mobile Test Automation