AI/ML Quality Engineering

Role description: Own the engineering delivery roadmap - Partner with customer leadership to define and execute technical roadmaps that balance speed, quality, and long-term maintainability, aligned to the customer's broader business goals. Lead AI-driven engineering transformation - Drive AI adoption across the engineering lifecycle, from developer tooling (AI-assisted coding, review, testing) through to embedding AI/ML into customer's products with a clear focus on cost optimisation and delivery velocity. End-to-end technical ownership - Take full accountability for the design, build, and delivery of highly available, scalable, cloud-native systems, ensuring reliability and performance at production scale. Collaborative cross-functional leadership - Work closely with the customer and partner teams (Product, Design, Engineering) to shape priorities, OKRs, and architecture decisions as one integrated team. Team leadership and capability building - Lead, mentor, and grow the deployed Zensar engineering team, embedding best practices in code quality, testing, and CI/CD, and building a strong team. Represent engineering in governance and planning - Contribute to customer's planning, budgeting, and leadership and executive reporting cycles; surface and resolve technical debt, bottlenecks, and cross-team dependencies early. Bring Zensar's advanced engineering practice to the customer's landscape - Act as the conduit for Zensar's broader engineering innovation, best practices, and accelerators, and participate in the customer's leadership forums as Zensar's senior technical voice. Champion culture and ways of working - Foster a healthy, inclusive, high-performing engineering culture across the combined Zensar & customer team Must be educated to at least degree level or equivalent.