What Cloud and GenAI hiring looks like in India is shifting at an unprecedented pace, perhaps more than other sectors, leaving students unsure of where the real entry points now lie. Much of the public conversation focuses on tools, but many employers are reorganising teams around new role structures, deeper skill expectations, and sharper filters for young talent. Companies across BFSI, healthcare, retail, and manufacturing are expanding cloud and AI workloads, and these shifts are opening specific types of early career roles that do not always match the hype cycle.
To help young readers see what the job landscape actually looks like inside companies, we spoke to CloudThat, a Bengaluru-based cloud training and consulting firm that works with enterprise teams as well as large cohorts of learners across India. Drawing on its view of both hiring demand and skills development, we tried to get a grounded picture of where roles are growing, what freshers typically do in their first year, and the gaps that may be holding candidates back.
1. From your specific vantage point, which job titles in cloud and GenAI are currently absorbing most freshers and young professionals in India?
From what we see at CloudThat, cloud adoption is a one-way migration. Once organizations move from on-premise systems to the cloud, it’s very difficult to move back. That decision fundamentally changes how technology teams operate. Development, infrastructure, data, and operations all move to the cloud, and the entire organization begins to function as a cloud ecosystem.
What this means in practice is that almost every technology role today needs to be cloud-aware. We’re seeing demand for cloud-aware developers, cloud engineers who operate cloud infrastructure, DevOps professionals, architects with multi-cloud experience, and data engineers working on cloud platforms. Cloud is no longer a niche specialization, it has become the baseline across roles.
At the same time, GenAI, cloud, and security are deeply interconnected. You can’t build or deploy GenAI without strong cloud foundations, and security teams now need to be both AI-aware and cloud-aware as well. This growing intersection of cloud, AI, and security is where fresher hiring is steadily concentrating today.
2. Across your enterprise clients, which industries are giving you the strongest signals of sustained hiring for these roles over the next two or three years, and which ones are slowing?
The strongest hiring signals we see today are from the BFSI sector. Nearly every major bank in India is working toward becoming digital-first, and that transformation depends heavily on cloud platforms, data, and AI. From our conversations with our BFSI customers, this segment alone shows a hiring intent of around 25%, particularly for cloud, data, and GenAI-related roles.
This direction mirrors global thinking as well. Jamie Dimon, Chairman and CEO of JPMorgan Chase, has openly stated that banks must continuously invest in technology and modernise their systems to remain competitive, especially against app-based fin-tech services. Indian banks are following that same playbook, committing long-term budgets toward technology modernisation and talent hiring.
In contrast, IT services companies have been more conservative in hiring over the past couple of years, largely due to macro and deal-cycle headwinds. However, this appears to be cyclical rather than structural. Recent media reports have shown early signs of a turnaround: Indian IT services firms recorded a 26% jump in deal wins in Q2, indicating improving demand visibility. As these deals move into execution, we expect hiring momentum to return, particularly to rebuild bench strength in cloud, data, and AI roles over the next two to three years.
3. How do these cloud and GenAI roles spread across Indian cities and regions? As in, across metros, large tier-two cities, and smaller locations?
Cloud and GenAI roles in India continue to be highly concentrated in tier-one cities, even as companies experiment with a wider geographic footprint. Metros such as Bengaluru, Hyderabad, Pune, Mumbai, and Delhi NCR remain the primary hubs for advanced and niche skills. This is where organisations place teams working on complex cloud architectures, core AI platforms, and high-impact global projects.
Recent investments underline this trend. Google’s new Ananta campus in Bengaluru, one of its largest offices globally, is designed to host thousands of engineers across Cloud, AI, and core product teams. OpenAI has also begun hiring in Bengaluru, marking its first formal India presence, while AI firms like Anthropic and Perplexity have publicly identified India, particularly Bengaluru, as a key base for scaling AI talent and adoption.
Tier-two cities are gradually seeing more opportunities, especially for standardised delivery, support, and implementation roles. However, for deep expertise in cloud, GenAI, and security, companies still rely on established metros that offer dense talent pools, stronger peer learning, and easier access to experienced professionals. Smaller locations remain limited to select functions, rather than core innovation work.
4. When freshers join cloud or GenAI-related teams inside companies, what kind of work do they typically handle in their first year, and how do these roles usually sit inside the wider team structure?
The kind of work freshers do in their first year depends largely on the size of the company. In large enterprises and consulting firms, roles are often very siloed. For example, on a large advisory engagement, I’ve seen teams where three or four people are assigned solely to manage cloud change requests, ensuring support tickets are raised, tracked, and closed correctly. While this provides exposure to enterprise environments, the scope of work is narrow.
In mid-sized and smaller companies, the experience is very different. Freshers are typically part of compact teams where senior members handle architecture and design, but younger professionals get exposure across the entire lifecycle, from requirements and implementation to testing and deployment.
For candidates who want faster learning and broader exposure, we usually recommend smaller or mid-sized organisations early in their careers. These environments offer a much more end-to-end, 360-degree view of how cloud and GenAI systems are actually built and run.
5. In your training and consulting work, which skill gaps keep showing up when fresh graduates move from classroom learning into real project environments?
One of the biggest gaps we consistently see is in soft skills. Things like writing clear emails, communicating effectively with teams, and having professional conversations are as important as technical abilities. Post-COVID, many colleges have relaxed attendance and shifted to remote learning, which has reduced opportunities for students to build real-world communication and collaboration skills.
On the technical side, the gap is largely about hands-on experience. Many students come in with strong theoretical knowledge of cloud and AI fundamentals, but without internships or real project exposure. This becomes a challenge when they encounter live environments with incomplete requirements, tight timelines, and real accountability.
Cloud and GenAI work is highly practical by nature. Without experience working on real systems, it takes freshers longer to adapt. Bridging this gap requires a stronger focus on applied learning, real-world scenarios, and exposure to how technology is actually used inside enterprises.
6. Based on what you see in the market today, what simple filters can a student or recent graduate use to judge whether a cloud or GenAI role is likely to offer growth and learning?
One of the simplest filters is how candidates use the interview itself. Most interviewers ask at the end, “Do you have any questions for us?” Many candidates skip this opportunity, but this is where real clarity comes from. I always encourage students to ask practical questions: What exactly will I be working on? What kind of projects will I be part of? How big is the team? What does success in this role look like in the first year?
The answers to these questions reveal a lot about whether the role offers growth or is narrowly defined.
Another important filter is company size. Larger organisations often offer stability but more specialised roles, while smaller and mid-sized companies typically provide broader exposure. Neither is right or wrong, it depends on what a candidate values. Making this assessment during the interview is just as important as reading the job description itself.
