Capgemini
QET and AI CoE Leader Location: PAN INDIA Grade : E1/E2 Role Summary The Artificial Intelligence Centre of Excellence (CoE) lead within the Quality Engineering & Testing (QE&T) business line is a senior leadership role responsible for defining the strategic direction, innovation roadmap, and industrialization of offerings and assets across AI-led Quality Engineering, Automation, SRE, Performance Engineering, DevSecOps, Security Testing, Mobile Testing, Test Data Management, and Test Ecosystem modernization. This role partners with Business, Delivery, Practices, Sales, and Technology organizations to drive differentiation, competitive advantage, and sustained practice growth. Additional Responsibilities: Strategic Leadership & Innovation: Define and execute the CoE strategy to advance the QE&T portfolio in alignment with market trends and technology evolution, particularly in GenAI and Agentic AI. Lead the creation and governance of offering roadmaps, frameworks, architectures, and transformation models. Drive innovation across AI, Generative AI/Agentic AI, Autonomous Testing, Cloud QE, and next gen automation technologies. Offerings & Asset Industrialization Develop, evolve, and industrialize multiple offerings across: AI & Autonomous Testing o Test Automation & Intelligent Automation o SRE & Reliability Engineering o Performance Engineering & Engineering Insights o DevSecOps & Secure SDLC o Security Testing o Mobile, API, and Cloud-native Testing o Test Data Management (TDM) & Test Environment strategies o Enterprise Test Ecosystem Engineering Ensure assets, accelerators, blueprints, and tools are scalable, reusable, and consistently embedded across delivery. Act as a key solution architect and subject-matter authority on large RFPs and strategic pursuits. Design innovative, value-driven QE&T solutions aligned with client needs and business outcomes. Partner with Sales and Bid Teams to craft winning strategies, solution narratives, estimation models, and delivery constructs. Delivery Excellence & Standardization : Drive the adoption of CoE frameworks, accelerators, and best practices across global delivery teams. Enhance delivery consistency, quality, and efficiency through standardized processes and industrialized solutions. Measure and improve asset usage, capability maturity, and customer value realization. Stakeholder & Ecosystem Leadership: Collaborate with Practice Heads, Delivery Leaders, CTO Organization, and Alliances to align strategies and accelerate adoption. Engage with technology partners, tool vendors, Hyperscale’s, and industry forums to strengthen the solution ecosystem. Support analyst engagements, client briefings, and thought leadership initiatives. People Leadership & Capability Development: Build and lead a high-performing team of architects, SMEs, technologists, and innovation leads. Develop capability uplift programs, learning paths, communities of practice, and a culture of engineering excellence. Mentor talent and foster continuous learning, curiosity, and innovation. Our Ideal Candidate: He / she / They or the incubment should have atleast 18+ years of experience in Quality Engineering & Testing, with deep expertise across multiple domains such as AI-led Testing, Automation, SRE, DevSecOps, Performance Engineering, Security Testing, and Test Ecosystem modernization. Proven leadership of Centers of Excellence, global practices, or large-scale QE transformation programs. Significant experience in pre-sales, solutioning, and supporting complex RFPs/pursuits. Demonstrated ability to industrialize offerings and embed solutions in large delivery organizations. Technical Competencies Strong understanding of: o AI/GenAI and automation frameworks o Cloud platforms (AWS/Azure/GCP) o CI/CD, DevSecOps, and modern engineering practices o TDM, TEM, and test ecosystem tools o Mobile, API, cloud-native, and microservices testing Proven experience driving engineering excellence and innovation across multi-technology landscapes. Leadership & Soft Skills Strategic thinker with strong business acumen and customer-centric mindset. Exceptional communication, executive presence, and stakeholder management skills. Ability to influence and collaborate across global matrixed environments. Strong problem-solving skills and a passion for innovation. Education: • Bachelor’s or master’s degree in engineering, Computer Science, or related field. • Preferred certifications: ISTQB Advanced/Expert, AI, Cloud Certifications (AWS/Azure/GCP), DevOps, SRE, Security, or equivalent.