Artificial intelligence is creating two distinct hiring tracks in the technology industry, with Indian IT services firms strengthening their technical talent pools to build and customise enterprise AI, while Big Tech firms are increasingly adding sales, consulting and go-to-market talent to drive adoption of their AI and cloud platforms.
The divergence reflects the different stages at which the two segments are operating in the AI value chain, even as both are increasingly converging on a new role that sits between technology and the customer -— the forward deployed engineer (FDE).
“As enterprise AI and cloud platforms transition from complex emerging tech into mainstream operational infrastructure, the go-to-market mandate for Big Tech has fundamentally shifted,” Milind Shah, managing director at Randstad Digital, said. “The priority is no longer just explaining how a technology is engineered, but articulating how it drives business transformation, operational efficiency, and ROI (return on investment).”
Anecdotal evidence suggests technology majors such as Meta and Amazon Web Services (AWS) are expanding entry and mid-level sales talent pipelines for client-facing roles in the UK and other markets. Internal AI copilot tools are also making it easier for sales professionals to understand complex architectures and pitch them to customers without necessarily having formal STEM backgrounds, Shah said.
A portion of this hiring is also moving to India, where the combination of lower costs and a rapidly expanding enterprise technology market is making the country an increasingly important base for Big Tech’s sales and customer-facing operations.
US Big Tech firms hired more than 30,000 people from India in 2025, and the number is expected to rise 16-20% in 2026, according to Neeti Sharma, CEO, TeamLease Digital. “Hiring is no longer just limited to engineering. Companies are building out enterprise sales, solution engineering, consulting and GTM leadership in India, increasingly tapping into consulting and B-school talent,” she said.
Yugal Joshi, partner at Everest Group, said some technical account management and non-client-facing sales roles such as prospecting, pre-sales and sales operations are increasingly being moved to India to lower the cost of sales and marketing.
However, “non-science” does not necessarily translate into non-technical. “Even a salesperson today needs a basic understanding of AI, cloud and technology to effectively sell these solutions,” Diwakar Chittora, Founder and CEO of online training platform, Intellipaat said. “Technology is no longer limited to computer science graduates. A sales professional may not need to build an AI model, but they need to understand what it does and how it solves a customer’s problem,” he emphasised.
Indian IT services firms, meanwhile, are moving in the opposite direction, placing greater emphasis on scientific and engineering talent as they seek to build the capabilities required to deliver AI-led solutions to enterprises. Companies are increasingly hiring PhDs, MTechs and engineering talent from institutions such as the IITs and IISc for areas including physical AI, agentic AI, advanced engineering and AI-led systems.
AI and AI-adjacent roles already account for a significant share of new hiring, while demand for machine learning operations (MLOps), AI engineering, production deployment and FDEs is rising sharply.
FDE postings have grown almost eightfold year-on-year, Sharma said. The shift is also visible in compensation, with leading IT firms offering freshers 20-25 lakh for elite AI engineering roles, compared with standard services entry packages of around3.5-4 lakh.
It captures that Indian IT requires scientific talent, not headcount at scale, Sidhant Rastogi, president of technology & business strategy at Zinnov, said. He estimates emerging AI opportunities could translate into $260-440 billion in technology services revenue by 2030 across data engineering, AI infrastructure, silicon engineering, AI governance and cybersecurity, and vertical AI.
The sharper technical requirements, however, are making these roles harder to fill. AI and GenAI engineering positions spanning MLOps, applied data science and integration of models into enterprise systems have consistently remained among the hardest-to-fill roles for IT services firms and GCCs in Bengaluru, Hyderabad and Delhi-Gurugram, according to Raghu S, a talent consultant for technology firms.
The apparent divergence, however, is beginning to converge around the FDE model, reflecting the next stage of enterprise AI adoption. Indian IT firms need technically strong talent to build and implement increasingly complex AI solutions, while Big Tech needs people who can take established AI and cloud technologies into enterprises and demonstrate their business value.
TCS, for instance, is building a cadre of up to 8,900 FDEs, equivalent to around 1-1.5% of its workforce, with the engineers expected to work closely with clients to accelerate AI adoption. Cognizant is training 5,000 frontier certified engineers alongside 10,000 frontier business operators.
In Big Tech, Google is hiring hundreds of FDEs across the US and Europe, Salesforce has committed to building a 1,000-strong cadre, while OpenAI has launched a dedicated deployment business.
The emergence of the role highlights how the AI jobs market is moving beyond the traditional distinction between engineering and sales. “Indian IT firms are hiring scientists to build the capability and Big Tech is hiring the people who make enterprises adopt it, and the forward deployed engineer, part builder and part translator, is where the two hiring strategies meet,” Rastogi said.