This article is based on an interview with Anand Sahay, CEO of Xebia, conducted by the Elets News Network (ENN). The original piece was published on digitallearning.eletsonline.com.
Why DevOps Matters Beyond the Buzzword
While artificial intelligence and automation dominate headlines, DevOps has quietly become one of the most consequential shifts in modern software engineering. DevOps is a culture and set of practices that unifies software development (Dev) and IT operations (Ops), enabling teams to deliver software faster, more reliably, and with fewer silos.
Digital transformation has changed buyer expectations across every industry. Companies must now ship software continuously, adapt to market signals quickly, and experiment without destabilising production systems. DevOps is the foundational practice that makes this possible. It encompasses automation of build, test and deployment pipelines; integration of security into the development lifecycle (often called DevSecOps); continuous feedback loops; and a cultural shift toward shared ownership of system reliability.
The Case for Formal DevOps Education
According to Sahay, computer science curricula at many institutions have not kept pace with industry practice. Course content that was relevant a decade ago may leave graduates needing significant retraining before they can contribute meaningfully to modern software projects. The result is a skills gap that employers — not educational institutions — end up paying to close.
Well-designed DevOps programmes should teach students:
- Software craftsmanship — writing clean, maintainable, testable code as a professional discipline.
- Automation mindset — identifying repetitive manual work and replacing it with reliable, version-controlled scripts and pipelines.
- Integrated security and testing — shifting quality and security checks left in the development cycle rather than treating them as gates at the end.
- Continuous delivery principles — designing systems and processes so that deployments are low-risk, frequent events rather than high-stakes releases.
- Design thinking — structured problem-solving and analytical approaches that connect technical decisions to user and business outcomes.
Sahay argues that for any computer science or IT student who intends to work on digital transformation projects, DevOps literacy is no longer optional — it is the bedrock of modern software practice.
Industry–Academia Collaboration: The UPES and Xebia Model
One practical response to the curriculum gap is direct collaboration between universities and technology companies. Xebia partnered with the University of Petroleum and Energy Studies (UPES) to co-design two full-time B.Tech programmes in Computer Science Engineering with specialisations in Big Data and DevOps, launched in the 2017–18 academic year.
Under this model, Xebia subject-matter experts helped shape the curriculum and train faculty, while also contributing industry perspective through seminars and tech talks. Both programmes included Design Thinking modules to build analytical and creative problem-solving skills alongside technical competencies. This kind of industry-designed curriculum is intended to reduce the gap between what students learn and what engineering teams actually need on day one.
Career Prospects in DevOps
DevOps consistently appears among the hardest technical roles for organisations to fill. The demand for skilled practitioners outstrips supply, which translates into strong employment prospects and competitive compensation for qualified engineers. Common DevOps career paths include:
- DevOps Architect — designs the overall CI/CD and infrastructure strategy for an organisation.
- Automation Engineer — builds and maintains pipelines, infrastructure-as-code, and testing automation.
- Security Engineer (DevSecOps) — integrates security tooling and practices into the software delivery lifecycle.
- Integration Specialist — connects disparate systems, APIs, and services to enable continuous delivery workflows.
- Site Reliability Engineer (SRE) — applies software engineering principles to operations problems, maintaining reliability at scale.
Sahay notes that even though DevOps has existed as a defined discipline for over a decade, the majority of organisations have not yet fully adopted its practices. That ongoing adoption creates sustained demand for engineers who can drive the transformation from within.
The State of Technology Education in India
Sahay is candid about structural challenges in India’s engineering education system. Syllabi at many institutions remain outdated, and the volume of practical, hands-on experience students receive is insufficient for the demands of contemporary software projects. While Massive Open Online Courses (MOOCs) provide valuable supplementary learning — particularly for working professionals seeking to upskill — they have not yet replaced the depth and structure of a well-designed undergraduate engineering programme.
A secondary challenge is awareness. Students and parents often default to conventional specialisations without understanding the career opportunities available in emerging disciplines like DevOps and Big Data. Bridging this awareness gap requires coordinated effort from universities, industry, and government.
Forward-looking private institutions are beginning to move faster than public universities on curriculum modernisation, partly because they have more flexibility to partner with industry. The Xebia–UPES collaboration is cited as an example of what becomes possible when companies invest directly in shaping graduate education rather than waiting to retrain hires on the job.
Emerging Technologies on the Horizon
Sahay identifies several technology areas as both current and forward-looking priorities:
Already Mainstream
- Artificial Intelligence and Machine Learning
- Blockchain
- Internet of Things (IoT)
- Extended and Virtual Reality
- Conversational AI (chatbots and voice agents)
Emerging Wave
- Quantum Computing — still largely in research and early experimentation, but expected to move toward commercial applicability over the coming decade.
In the Indian context, Sahay observes a growing startup ecosystem driving domestic innovation in AI, deep learning, analytics, and IoT — a meaningful shift from the historical pattern of India primarily consuming rather than creating technology. Traditional enterprises are also adapting, moving toward fully digital operating models and becoming more receptive to experimentation.
India’s Strengths, Weaknesses, and the Innovation Imperative
Sahay reflects honestly on systemic barriers to innovation in India. Despite a large pool of technically capable graduates strong in mathematics and science, India has historically imported rather than originated core technologies. He attributes this partly to cultural and social pressures that push talented individuals toward conventional, risk-averse career paths, and partly to insufficient research funding and infrastructure for those who do pursue deep technical work.
The good news is that the startup ecosystem is beginning to change this dynamic. More young engineers are building products rather than just services, and investor attention to deep-tech sectors is growing. Sahay sees this as the foundation for India becoming a genuine source of global technology innovation rather than primarily an execution partner.
The Evolution of India’s IT Workplace Culture
Drawing on his own career, which began in the late 1990s when Indian IT labour was first gaining global recognition, Sahay traces a significant arc: from maintenance and support work with low innovation expectations, through large turnkey delivery projects using process frameworks like CMMi, to today’s environment where Indian engineering teams are increasingly expected to contribute product innovation, not just execution.
Workplace culture has shifted correspondingly — from hierarchical, command-and-control structures toward smaller, autonomous, Agile teams. Management roles are evolving from directive oversight to impediment removal and support, a model more aligned with how high-performing engineering organisations operate globally. Sahay sees this as a positive and continuing trend.
Key Takeaways for DevOps Practitioners and Hiring Managers
- DevOps skills remain in short supply relative to demand, making it a strong career investment for engineers at any stage.
- Organisations that have not yet adopted DevOps practices represent the next wave of transformation opportunity — and the next wave of hiring.
- Industry–academia partnerships can meaningfully improve graduate readiness, but require sustained commitment from both sides.
- MOOCs are well suited for professional upskilling but should complement, not replace, structured engineering education at the undergraduate level.
- Emerging technologies like AI, IoT, and Blockchain are already creating adjacent demand for DevOps engineers who understand how to deliver and operate these systems reliably.