The Great Divide: A Two-Tier Market
India's AI employment landscape is splitting into two separate worlds. The top tier is a high-demand, high-salary bracket reserved for experienced professionals who can build, deploy, and manage complex AI systems. These are the architects and senior
engineers with proven track records. The second tier is a hyper-competitive space for entry-level talent and those with limited practical skills. A recent Nomura report highlights this trend, noting that while demand for senior workers is strong, companies show weaker demand for entry-level employees. An ICRIER survey cited in the report found that 55% of IT firms reported a decline in entry-level hiring, compared to just 14% at the senior level. This creates a scenario where thousands of AI-related jobs are being created, but freshers find it increasingly difficult to secure them.
Why Experience Commands a Premium
Companies are moving past the experimental phase of AI and into full-scale implementation. They need professionals who can deliver tangible business results, not just theoretical knowledge. As firms automate routine tasks previously handled by junior employees, they are prioritising candidates with specialised AI expertise who require less on-the-job training. The focus has shifted from academic credentials to a demonstrated ability to solve real-world problems. Employers are now looking for skills in areas like Generative AI, MLOps (Machine Learning Operations), and cloud platform deployment. This shift means the traditional career ladder, where graduates learned on the job, is being disrupted. Companies are willing to pay a premium for specialists who can immediately contribute to productivity, with experienced GenAI engineers often commanding salaries 25-45% higher than their peers.
The Fresher's Dilemma
For new graduates and those looking to transition into AI, the market presents a classic catch-22: you can't get a job without experience, and you can't get experience without a job. While overall AI-related hiring in India is outpacing job losses by a significant margin—with 83,100 hires versus 31,921 layoffs according to Nomura—these new roles are not being filled by the same pool of workers. The jobs being eliminated, often in customer support or back-office operations, do not provide the skill set for the new AI engineering roles being created. This leaves freshers competing for a smaller number of entry-level positions. Fresher salaries for AI engineers typically range from ₹6-9 LPA, but the competition is fierce, with hiring managers reporting that fewer than 10% of applicants demonstrate job-ready skills.
How to Bridge the Experience Gap
For aspiring AI professionals, the key is to build a portfolio of practical, demonstrable work. Employers are increasingly prioritising skills over degrees, with project-based hiring on the rise. Jobseekers should focus on gaining hands-on experience through internships, freelance projects, and contributions to open-source AI initiatives. Building and shipping a project, especially using technologies like Retrieval-Augmented Generation (RAG) for GenAI, can make a portfolio stand out. Upskilling in high-demand specialisations such as MLOps, LLM fine-tuning, and AI system design for cloud platforms like AWS or Azure is also critical. While certifications can help, the emphasis must be on application. Employers are no longer asking what you studied; they are asking what you built and what problem you solved.
