As India celebrates National Engineers’ Day, technology leaders are highlighting how engineering is evolving alongside artificial intelligence (AI), with sustainability, efficiency, reliability and responsible technology development emerging as key priorities.
Simon Rizkalla, Vice President, Customer Advocacy APJ, New Relic, said sustainability needs to be as central to engineering conversations as innovation. He highlighted the company’s GreenOps approach, which focuses on improving infrastructure efficiency while reducing the environmental footprint of workloads.
New Relic set a goal to achieve net-zero emissions by 2030, with targets approved by the Science Based Targets initiative. Rizkalla said migrating the company’s largest workloads from on-premises data centres to AWS Graviton-based instances reduced emissions from those workloads by 37 per cent.
He noted that AI represents the next frontier for sustainable engineering. Intelligent observability can help engineering teams identify inefficient AI workflows, such as agents making multiple model calls for tasks that require fewer calls, thereby reducing both computing requirements and costs.
Abhilash Shetty, Vice President & Head of Engineering & AI, Visionet, said the role of engineers is evolving as AI and emerging technologies reshape systems and business processes. With AI democratising access to knowledge and expertise, engineers are increasingly required to frame better questions, challenge conventions and convert insights into meaningful outcomes.
Praveer Kochhar, Co-Founder and CPO, KOGO AI, stressed that sustainable AI engineering also involves reducing duplicated infrastructure and improving governance. He said enterprises can end up operating multiple disconnected AI tools for retrieval, evaluation, observability and governance. Consolidating these capabilities can reduce redundant computing, integration work and operational risk.
Meanwhile, Subhash Kalluri, Founder, FreJun, emphasised the importance of reliability in engineering. He said engineers often work behind the scenes to make complex technologies dependable and easier to use, with AI-powered voice infrastructure being one example where engineering is helping make AI agents suitable for everyday business applications.
The perspectives underscore a broader shift in engineering: from simply building new technology to developing AI systems that are efficient, sustainable, reliable, governed and capable of delivering measurable business impact.
