In an exclusive interview with CXOToday, Chandan Govindarajulu, Executive Vice President, Global Delivery & Business Leader at Virtusa Corporation, discusses how enterprises are moving from traditional application development toward AI-native product engineering.

The conversation explores how organizations can re-engineer the software development lifecycle (SDLC) to move beyond transactional, one-off software projects and toward continuously evolving products and platforms. According to Chandan, Virtusa’s product engineering heritage shapes its approach to enterprise technology, with the focus shifting from “building software to spec” to owning self-evolving products powered by AI and deep domain differentiation.
The discussion highlights the growing importance of modular, configurable and reusable platforms. Rather than creating isolated applications that contribute to technical debt, fragmented data and higher maintenance costs, enterprises can establish unified context layers that enable greater scalability and support autonomous AI workflows.

Chandan also explains how AI is transforming the software engineering lifecycle across greenfield development, brownfield modernization, support and quality engineering. AI-driven workflows can translate business intent into structured requirements, generate code, support refactoring and code reviews, and enable agent-driven testing. The model also extends into autonomous operations, where AI agents can monitor telemetry, triage incidents and support self-healing environments.

The impact extends beyond developer productivity. AI-native engineering can reduce cognitive and operational toil, helping organizations compress delivery cycles and move market-ready capabilities from concept to production in significantly shorter timeframes. The approach also enables engineering teams to focus more of their expertise on architecture, security, user experience and other high-value areas.
The interview further examines the changing role of technology partners. As enterprises adopt platform engineering and AI-native transformation, partners are increasingly expected to bring reusable assets, AI harnesses and domain frameworks while contributing to shared ownership of innovation, outcomes and long-term business value.

Another key focus is the evolution of Global Capability Centers (GCCs). The conversation highlights how GCCs, particularly in India, are becoming strategic hubs for product engineering, innovation and product ownership. To support this evolution, organizations need capabilities spanning end-to-end product ownership, AI-native software development, talent transformation and domain-specific value orchestration.
The interview concludes by examining what will differentiate organizations that successfully scale AI-led product and platform engineering. Beyond isolated developer productivity gains, market leaders will focus on faster innovation, stronger customer experiences and lean, high-rigor AI-native engineering teams.

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