Same headcount, 4x pay: tech hiring splits in two

HCLTech closed its FY27 campus programme at roughly 11,000 freshers, similar to FY26, but split the cohort into two very different pay bands. Elite Engineers from IITs and NITs, targeting semiconductor and silicon, AI, data engineering, physical AI and robotics, and quantum, start at Rs 18 lakh a year. The mass Primus route across 60-plus partner colleges starts at Rs 4.5 lakh and tops out at Rs 10 lakh for Polaris, based on cognitive, coding, technical and English assessments. Chief People Officer Ram Sundararajan framed it as a pivot to skills-based hiring.

Teksands take: Flat headcount with a 4x internal pay spread is the clearest statement yet that the IT services pyramid is being rebuilt rather than refilled. The volume tier still exists, but it is now priced and assessed like a commodity. The frontier tier is priced above what many mid-level engineers earn. If your campus plan still runs one salary band and one assessment, you are not competing for the Elite cohort at all — you are supplying it to someone else.

Draup's analysis of Fortune 500 job postings finds AI Builder roles have more than doubled since 2021 to 27% of technology demand, while support- and experience-heavy roles lose share. AI skills have spread well beyond engineering: 68% penetration in IT, 61% in engineering R&D, 31% in support, 25% in sales, 21% in finance and 20% in HR. The entry-level pathway is narrowing — internships and contract roles now account for 27% of early-career hiring, up from 13% in 2020, and average internship length has stretched from 3.6 to 9.7 months. Since generative AI went mainstream in late 2022, employment for ages 35-40 is up 11.4% while ages 22-25 are down 2.4%.

Our take: The 27% is the demand signal. The 13%-to-27% shift in early-career hiring is the structural one. If Fortune 500 buyers keep converting fresher intake into extended internships and contracts, the pyramid model that Indian IT services and GCCs were built on gets more expensive at the base, not less. And the 22-25 age band shrinking while 35-40 grows tells you where the entry door is closing. Campus volume targets are the wrong metric now.

Disney cut 300 tech and HR roles in the same week it hired its first CTO

Disney eliminated roughly 300 roles across technology and HR, its third round of cuts this year, after earlier reductions of about 1,000 marketing staff and several hundred across Pixar, ESPN and National Geographic. The cuts follow an employee buyout programme and arrive as new CEO Josh D'Amaro pushes toward a tech and AI-led operating model. Disney has hired Karandeep Anand, former Character.AI CEO, as its first chief technology officer, and has posted a Director of AI Enablement and Legal Engineering role. The piece cites Bloomberg reporting that US employment-services headcount has fallen about 18% since ChatGPT launched, and layoffs.fyi data putting 2026 tech layoffs near 130,000, already above 2025's full-year total.

This is not a contradiction, it is a reallocation. Disney is cutting technology and HR roles that AI and centralised platforms can absorb, and paying premium for AI leadership instead. Indian GCCs and IT services firms that staff large HR operations and generalist tech benches for global clients should expect the same mix shift in FY27 demand. Protect AI engineering, platform and automation talent. Treat repeatable HR ops and legacy support roles as efficiency plays, not growth headcount.

Four signals worth watching

The lesson: The 'fresher salary' as a single number is dead. It is now a range that spans from commodity to specialist inside one batch. TA leaders should stop benchmarking against one campus figure and start benchmarking against the specific skill cluster they are hiring for. And anyone hiring at the bottom of that range should assume the candidate knows exactly where the top of it sits.

India's pedigree premium flatlines while UK employers keep hiring — for different skills

Hiring for the top of the band, not the middle of the pyramid

The records this week point the same way: demand is concentrating in AI builders, security, data and platform roles, while repeatable execution work gets cheaper, more temporary and more automated. Teksands works with GCCs, IT services firms and product companies to hire for that concentrated demand — AI engineering, data, cloud, cybersecurity and the AI-fluent business roles that now sit alongside them.

Run a two-band audit on your open tech requisitions this week

Take every open technology requisition and mark it frontier, AI-fluent or repeatable. Then check three things against that label: the compensation band, the work-model policy, and the assessment used to screen. If a frontier AI role and a repeatable support role share the same band, the same office mandate and the same screening test, you have found the reason your specialist offers keep getting declined. The records this week show employers splitting pay 4x inside a single fresher batch and segmenting work models by role. Do the same segmentation on your own requisitions before your next offer cycle.