Inside Indian IT's Scramble to Build an Army of Forward Deployed Engineers

When Tata Consultancy Services reported its June-quarter earnings earlier this month, one announcement stood out beyond the company's $9.5 billion order book and $2.6 billion annualised AI revenue run-rate. India's largest IT services exporter plans to build a workforce of forward deployed engineers (FDEs)—or "rapid build engineers", as it calls them.

FDEs combine domain understanding, implementation experience, and technical depth to embed AI directly into the workflows of enterprise clients.

TCS aims to eventually have about 1% of its workforce in these roles, implying nearly 6,000 engineers based on its June-quarter headcount.

The move reflects a broader rush inside India's IT services industry to catch up to AI giants that threaten to upend its traditional systems integrator function by embedding their own specialised engineers into client offices for an AI-native transformation.

OpenAI created the OpenAI Deployment Company, a new venture backed by more than $4 billion in investment. Anthropic is making an enterprise push with a $1.5 billion enterprise AI venture. Microsoft also recently announced a $2.5 billion ‘Frontier Company’ unit, staffed by 6,000 FDEs. 

TCS is not alone. This earnings season, nearly every major Indian IT services company has spoken about building similar client-facing AI engineering teams that work inside customer environments, understand proprietary data and business workflows, and accelerate enterprise AI adoption.

Indian IT Taps FDEs

Under CEO Venu Lambu, LTM’s AI1000 initiative is targeting 1,000 forward-deployed AI engineers, part of a wider AI business.

"Our AI pivot is now producing tangible proof points for clients, visible in the outcomes we are creating and in the size and nature of the engagements we are winning," Lambu told analysts post Q1 FY27 results, pointing to a strong order book and pipeline as evidence the strategy is converting into actual deals.

During the June quarter, LTM boasted an order book of $1.7 billion featuring two large deals. Its AI revenue was $150 million on a quarterly run-rate basis.

"This year, the buzz was around AI creation—what does AI do, what kind of models are there. Now the conversations have moved from appreciating AI creation... to AI deployment. So now, as those conversations get real, there is a strong demand for FD engineers in the ecosystem," Lambu noted.

Infosys has also announced similar plans. “We are building a team of frontier engineers to support client work. Our plan is to have 6,000 frontier engineers over the next few years,” CEO Salil Parekh said during a post-earnings press conference.

Cognizant, on the other hand, rather than adopting the FDE label, has unveiled a "frontier workforce model" split into two tracks: 5,000 Frontier Certified Engineers, who build and stay accountable for agentic AI systems after they go live, and 10,000 Frontier Business Operators, who run day-to-day operations in environments where human staff and AI agents work side by side.

Meanwhile, HCLTech’s Chief People Officer Ramachandran Sundararajan said the company is building a dedicated pipeline of FDEs, adopting a "build and buy" strategy that relies primarily on internal AI skilling alongside selective lateral hiring for immediate needs.

Old Wine in a New Bottle?

The near-simultaneous move by competing firms has prompted analysts to ponder whether this is a genuine revamp of business model or if IT firms are just rebranding existing consulting work.

Gaurav Vasu, Founder and CEO of the market research firm UnearthInsight, traces the industry-wide push back to failed AI pilots. 

"The only way you can [close that gap] is when you bring a subject matter expert," he says, describing the forward deployed engineers as effectively "enhanced functional consultants" who pair domain knowledge with technology fluency, at a moment when coding itself has been commoditised by large and small language models. 

There is no differentiation left between a junior developer and a seasoned technologist purely on coding ability, he notes, because AI has put that skill "in the hands of everybody." The only value services firms can still sell, in his view, is domain expertise fused with the ability to actually ship AI into a live, messy enterprise environment, architecting the stack, cleaning the data, building integration layers, and staying accountable long after deployment.

Even so, Vasu is unambiguous that this is not a new business model. 

“Clients will still need nuts and bolts. Are we saying that your clients won’t need SAP, Oracle, or Workday, and they will straight away move to applications built by a [FDE] team? I don't think so,” he says, remarking that FDEs are just another value-added service.

What is changing, according to him, is that the forward-deployed layer sits additively on top of that same client relationship, commanding a premium, even as hyperscalers, frontier AI labs, and services firms compete for the same talent while also partnering with one another on shared client accounts.

Other analysts see something closer to structural change. Aditya Narayan Mishra, Managing Director and CEO of CIEL HR Services, reveals that the demand for FDEs has grown by more than 130%, with total demand in the first quarter of 2026 alone already exceeding everything recorded across all of 2025. 

He expects the shift to flatten organisational structures over time. “AI projects increasingly require smaller groups of specialists who can engage directly with clients, understand business problems, and rapidly deploy solutions. Over time, we are likely to see flatter delivery structures, stronger consulting capabilities, and a larger share of revenue coming from outcome-led AI engagements,” says Mishra.

Meanwhile, Saravanan Balasundaram, Founder and CEO of Han Digital Solutions, frames the shift in blunter terms, close to describing it as an existential response for the sector.

"Customer demand has clearly shifted from staff augmentation to AI-driven outcomes. With agentic AI increasingly taking over work traditionally billed by the hour, IT services companies are being forced to move beyond the conventional time-and-materials model. Moreover, for the last few years, AI is also maturing and getting ready for mass production rollouts. Indian IT's entire commercial model is under pressure. Hence, IT firms see this role as essential for delivering measurable outcomes to stay relevant,” Balasundaram says.

Talent Math Doesn't Add Up

The harder question is whether the talent to staff these ambitions exists at all. According to research by talent solutions firm Xpheno, the potential talent pool for FDEs in India is around 2,800. 

Against that baseline, an industry collectively chasing totals in the tens of thousands looks less achievable.

Per CIEL HR Services, only around 12% of the current entry-level talent pool is prepared for AI and machine-learning roles at all, let alone the broader consulting and client-facing skills a forward-deployed role demands on top of that.

However, the demand for FDEs is strong. According to TeamLease Digital, the demand for FDEs increased by nearly 800% between Q1 FY26 and Q1 FY27. 

Retention Isn’t a Given

Even if companies succeed in building these teams, keeping them may prove harder still. Analysts agree that compensation alone will not be enough to hold forward-deployed talent against the pull of hyperscalers, AI labs, and product companies, some of which are paying upward of $300,000 to $600,000 for the role in North America.

According to TeamLease Digital, Indian firms are offering fat packages for these roles. While entry-level FDEs can earn ₹18–25 lakh per annum, senior roles can fetch up to ₹85 lakh or more. 

Mishra says retention will hinge on offering "a strong learning environment, greater ownership and faster exposure to high-impact AI programmes" rather than pay alone. “These roles naturally command higher pricing because they influence business outcomes,” he remarks. 

Balasundaram is more sanguine about the immediate risk, arguing the market is still too nascent for poaching to be the dominant story yet, and predicts India's FDE talent pool could grow beyond 20,000 in the coming years, with domestic IT firms potentially becoming "talent factories for the AI economy" that produce more FDEs than they ultimately retain.

India's largest IT services companies are making the same wager that the next phase of enterprise AI adoption will be won not by whoever has the best underlying model, but by whoever can embed the smallest number of the right people inside a client's business to make that model actually work.