Mid-tier IT services company LTM is seeing a total collapse of entry-level engineering roles as artificial intelligence (AI) changes the way companies operate, services are delivered and enterprises seek greater efficiency across their value chains.
Such roles, mainly L0 to L2, classified as basic engineering functions, have been under threat ever since machines started writing thousands of lines of code and functions across the software development life cycle (SDLC) started getting compressed as AI merged many functions.
“Any new deal that we bid for, we never put a L0 role,” Gururaj Deshpande, Chief Delivery Officer, told Business Standard in an interaction.
“We started to think what if you just collapse the layers across L0 to L2 and bring in good AI native thought process on the model itself. When you bring in AI in its true might with a proper AI native type of an architecture, it will start to change the game. To complete that we had to build a tool set which brought in the power of all of this. In fact, the first thing I had to do was throw out all of the old tooling. So changing the operating model meant that I need to have new roles as I can’t be doing things in my old way.”
Such roles include AI support engineers, AI architects and tokenomic experts, to name a few, as traditional testing, maintenance and quality assurance roles wither away. With heavy automation, human engineers are expected to supervise and verify the work of machines rather than doing those tasks on their own.
“An AI support engineer is more like the human in the loop. He is less of the doer but more of the checker so part of my operating model was around building a tool and then then identifying the skill set in terms of people that will have to hire,” said Deshpande.
With AI baked into all deals, both new and renewals, services companies are also looking for engineers with new skill sets rather than traditional ones. That is also leading them to hire more at the bottom of the pyramid, which allows them to take in AI-native engineers at a lower cost. LTM, for example, expects to hire at least 6,000 fresh graduates this year even as skills, roles and career paths change.
Besides talent reimagination, pricing models are also changing, albeit at a slower pace. From the traditional time-and-material (T&M) model, companies are looking for more fixed-price and outcome-based pricing.
“We want to push towards outcome based models but that shift will not happen overnight. Many clients will still want to keep control. They still want to run T&M so there’s an ongoing dialogue with customers on engagement models,” he added.
On AI rate cards, he said the conversations were ongoing. “I don’t think either everybody will come wholeheartedly and want to sign a rate card nor do we want to keep operating under the same rate card. I think we also have to stand up to clients and say if you really need a hyper productive engineer from day one to hit the ground with awareness of all the tools, you have to pay for it.”
LTM’s total headcount at the end of Q2FY27 was 88,835. Attrition for the quarter stood at 13.3 per cent.
