- AI engineering job postings in India grew +59.5% YoY, the highest among markets studied, including the US, UK, France, and Germany.
- While Bengaluru and Hyderabad continue to anchor hiring momentum as leading metros, growth is increasingly extending beyond them into emerging cities like Vijayawada.
- Fastest-growing AI skills amongst SMBs in India include AI Agents, AI Productivity, Azure AI Studio reflecting rising demand for applied, execution-focused capabilities.
Hiring for AI talent in India has grown 59.5% year-on-year, according to LinkedIn’s new AI Labor Market Report 2026. While Bengaluru continues to lead as a global AI hub, the report highlights a shift in hiring momentum for AI talent. Cities such as Hyderabad (+51%) and Vijayawada (+45.5%) are seeing strong growth in AI engineering hiring, signalling a broader spread of opportunities across tier-2 and tier-3 markets.
AI adoption across industries and companies is accelerating demand for AI talent
The growth in AI engineering hiring is being driven by rapid AI adoption across organisations of all sizes. Large enterprises continue to lead employing the highest share of AI talent as they invest in infrastructure, governance, and large-scale deployment. At the same time, smaller and mid-sized businesses are catching up quickly, serving as a bridge between early experimentation and enterprise-scale adoption. AI talent supply is also expanding across industries as adoption deepens. In manufacturing, AI engineering talent has expanded 4x in India reaching 2.0% in 2025.
Malai Lakshmanan, Head of LinkedIn India Engineering, says, “We are seeing strong growth in applied AI skills such as AI agents and productivity tools, which are directly tied to real-world deployment. For engineers, this is a clear signal to focus on building practical, hands-on capabilities and integrating AI into everyday workflows. As adoption accelerates across industries and organisations of all sizes, those who can move from experimentation to execution will be best positioned to capture the opportunity.”
Applied AI skills reshaping hiring across sectors
Skills such as AI Agents, AI Productivity, Azure AI Studio, Intelligent Agents, and Automated Feature Engineering are seeing strong demand in the SMB sector indicating capabilities that professionals must invest in to future-proof their careers. In industries such as manufacturing, AI Agents and AI Prompting are emerging as critical skills to strengthen employability.
LinkedIn India’s Head of Engineering, Malai Lakshmanan, shares tips to help engineers tap into growing AI opportunities:
- Build in-demand AI capabilities: Focus on developing skills in fast-growing areas such as AI tools, data, and applied problem-solving that employers in your industry are increasingly demanding.
- Be targeted in your AI-led job search: Prioritise roles where your skills align closely with the job’s requirements, and use AI tools to assess your fit upfront. Features like LinkedIn Job Match can show how well your profile matches a role, helping you focus on opportunities where you’re most likely to succeed
- Demonstrate real-world application: Highlight projects, tools, and examples that show how you have applied AI techniques to solve problems and deliver outcomes. Verifying your skills, such as AI tools you use like Loveable or Replit, can also help employers quickly see your capabilities.
Methodology
AI Talent A LinkedIn member is considered AI talent if they add AI skills to their profile and/or they have ever held an AI occupation.
The LinkedIn Hiring Rate (LHR) is a measure of hires divided by LinkedIn membership in the country. This analysis looks at the changes in hiring rate between this month and the same month in the previous year. This is based on members’ profile updates using the start date of a new job.
LinkedIn AI job posts. A job post is labelled as requiring AI talent if it either (i) lists at least two AI engineering skills, or (ii) is associated with an AI occupation. Talent demand is defined as the proportion of all job posts in a country that meet these criteria.
AI Talent Concentration. The counts of AI talent are used to calculate talent concentration metrics, e.g., to calculate the country-level AI talent concentration, we use the counts of AI talent in a country divided by the counts of LinkedIn members in that respective country.
GAI-Exposure Occupations. Augmented occupations require a mixture of skills that are GAI replicable and human-centric, disrupted occupations utilize skills largely replicable by GAI, and insulated occupations use few GAI replicable skills.
Company size. For analysis by firm size, companies are classified as Micro (1–10 employees), SMBs (11–500 employees), and Enterprise firms (501+ employees).
Disclaimer: This is a press-release.