Software engineering and AI salaries in India 2027: what each role pays

How to read these tables

Every range below is SYTalent Market Data on annual fixed pay for 2027, in ₹ lakh unless marked crore. Fixed pay means recurring base only, excluding variable bonus, joining bonus and equity. The reference market is Indian product companies and global capability centres in Bengaluru; the employer and city sections show how to adjust from there.

Levels follow years of relevant experience: entry 0 to 2 years, mid 3 to 5, senior 6 to 9, staff or lead 10 to 14, and principal or leadership 15 and above. A blank cell means the role is rarely hired at that level. Read the level from scope, not title: a "senior engineer" at a services firm is often a mid-level hire at a product company.

Software engineering salaries in India, 2027

A backend engineer in India earns about ₹10 lakh to ₹20 lakh at entry, ₹22 lakh to ₹42 lakh at mid level, ₹40 lakh to ₹75 lakh at senior level and ₹65 lakh to ₹1.1 crore at staff level, on SYTalent Market Data. Backend, platform and data engineering sit at the top of the individual contributor ladder; QA and test sit at the bottom.

SYTalent Market Data, 2027 fixed pay, individual contributors (₹ lakh per year)

Read the backend row against our FinTech salaries in India 2027 benchmark, which puts a fintech backend engineer at ₹26 lakh to ₹49 lakh fixed at mid level. Fintech sits slightly above this reference market at the same level because of domain scarcity in payments, ledgers and fraud.

SYTalent Market Data, 2027 fixed pay, engineering leadership

A CTO's pay depends more on company stage than on years. Our fintech benchmark puts a CTO at ₹1.1 crore to ₹2 crore in cash at seed to Series A and ₹2 crore to ₹3.3 crore at Series B to C, with pre-IPO and large listed companies above that, and the same shape holds across Indian technology companies.

AI salaries in India, 2027

An AI engineer building applied LLM systems in India earns about ₹22 lakh to ₹40 lakh fixed at mid level and ₹38 lakh to ₹60 lakh at senior level, on SYTalent Market Data. The highest-paid individual contributor seats are LLM and foundation model engineers, inference engineers and applied or research scientists with a publication or production record.

SYTalent Market Data, 2027 fixed pay, AI engineering and science (₹ lakh per year)

SYTalent Market Data, 2027 fixed pay, AI architecture, product and leadership

These AI ranges align with our existing role estimates: AI jobs in India puts an AI engineer with two to eight years at ₹18 lakh to ₹60 lakh, an agentic AI solution architect at ₹45 lakh to ₹90 lakh and an enterprise AI architect at ₹60 lakh to ₹1.2 crore. The forward deployed engineer and Head of AI guides carry the level-by-level detail, including ₹80 lakh to ₹1.5 crore in cash at funded startups for a Head of AI, with significant equity on top. Chief AI Officers at the largest employers can sit above the leadership range shown.

The data scientist row sits below the ML engineer row at every level, because employers pay more for shipping models than for building them in notebooks. Fintech versions sit higher again: a fraud or credit ML engineer at ₹45 lakh to ₹80 lakh on our fintech benchmark. Our page on AI jobs in fintech and banking explains why the problem, not the technique, carries the premium.

How pay differs by employer type

Employer type is the largest single variable in Indian technology pay. On SYTalent Market Data, IT services pay roughly 0.55 to 0.75 times the reference market in the tables above, while Big Tech pays 1.2 to 1.5 times in cash before RSUs, and trading firms more again.

SYTalent Market Data, indicative fixed-pay multiplier against the reference market

Aon's Annual Salary Increase and Turnover Survey for India 2026-27, released on 14 October 2026, explains why the services gap is widening rather than closing. It projects 2027 increases of 6.6 per cent in technology consulting and services, against 9.4 per cent at GCCs and 9.5 per cent in technology platforms and products.

Trading firms are a separate market. Our HFT and quant salaries in India benchmark puts quant development and core engineering freshers at top India-based firms at ₹30 lakh to ₹55 lakh in total first-year compensation, well above any entry cell here. The cost to hire comparison sets these Indian ranges against US, UK and Singapore pay.

City differences: Bengaluru, Hyderabad, Pune, Delhi NCR, Mumbai and Chennai

Bengaluru is the baseline for software and AI pay in India. On SYTalent Market Data, Mumbai sits level or slightly above for technology seats, Delhi NCR at or just below, Hyderabad 10 to 15 per cent below, and Pune and Chennai 15 to 20 per cent below.

SYTalent Market Data, technology pay against Bengaluru

These are the same technology adjustments as in our fintech benchmark. Two cautions apply. The discount compresses sharply at senior and leadership level, where the pool is national and candidates relocate or work hybrid. And Hyderabad's GCC concentration means a senior AI or platform seat there is often priced at Bengaluru levels by employers competing for the same people.

Variable pay, ESOPs, RSUs, joining bonuses and buyouts

Fixed pay is only part of a senior offer. Variable pay, equity, joining bonuses and notice-period buyouts can together add a large share on top, and the mix differs sharply by employer type.

Variable pay. Usually a target percentage of fixed, paid annually against company and individual performance. It is low at entry level and rises with seniority; leadership roles carry the largest variable share.

ESOPs and RSUs. Startups and unicorns grant ESOPs, which are illiquid until an IPO, secondary sale or buyback. Big Tech and many GCCs with listed parents grant RSUs that vest on a schedule and can be sold. A candidate comparing ₹60 lakh of startup cash plus ESOPs with ₹65 lakh of GCC cash plus RSUs is comparing different liquidity, not just different numbers.

Joining bonuses. Common for senior and scarce AI hires, typically used to compensate for a forfeited bonus or unvested equity. They usually carry a clawback if the hire leaves within a year.

Notice-period buyouts. Long notice periods are standard at many Indian employers, and a buyout lets the hire join sooner.

The AI premium: why AI seats pay more

AI seats pay more than equivalent software seats because the pool of engineers who have run AI systems in production is far smaller than the pool who have experimented with them. On SYTalent Market Data the premium is roughly 10 to 25 per cent at the same level, and it attaches to specific skills rather than to a title.

Aon's 2026-27 India study reports talent premiums for AI, machine learning and data science roles increasing by approximately 10 per cent from 2025, alongside continued investment in agentic AI. From our desk, the premium is concentrated in four capabilities:

• Production LLM systems. Retrieval, context management, guardrails and cost control in a live product with real users, not a demo.
• Evaluation. Building test sets, automated evals and regression checks that tell a team whether a model or prompt change made things better or worse.
• Inference optimisation. Quantisation, batching, caching and serving on GPUs to cut latency and cost per request.
• Agent orchestration. Multi-step agents with tool use, state, failure handling and human review, which is where most enterprise AI budgets are now going.

Candidates who can show eval results, latency gains or cost savings from a system they owned command the premium; those who only list frameworks rarely do. Our AI, deeptech and quantum talent search practice runs these searches, and the jobs board lists current openings.

The 2027 increment outlook

Aon projects Indian salaries to rise 9.1 per cent in 2027, against a 9 per cent actual increase in 2026, in its Annual Salary Increase and Turnover Survey for India 2026-27, released on 14 October 2026 and covering more than 1,200 organisations across 45 industries.

Source: Aon, Annual Salary Increase and Turnover Survey for India 2026-27, October 2026. The same study reports overall attrition of 18 per cent in 2026, up from 16.2 per cent in 2025.

Two practical points follow. A flat increment budget will under-price AI talent, because the premium is moving faster than the average. And attrition rising to 18 per cent means more counteroffers, so plan for offers above standard budget for scarce seats.

Methodology: how these estimates are formed

There is no public census of Indian software and AI pay by role and level. The ranges on this page are SYTalent Market Data, formed qualitatively and stated as ranges rather than medians.

Search and offer conversations. The primary input is what we see across our talent search work for a client base of 65+ clients and a 50K+ talent network: the packages candidates hold, the offers employers make and where offers are accepted or declined. We do not publish counts from these conversations, and no figure on this page is a statistical median.

Published data, read for direction. We read institutional salary-budget surveys from Aon, Payscale and TeamLease for growth rates, and employee-reported platforms such as Glassdoor and Levels.fyi for direction and spread. We do not reproduce them: self-reported data is unaudited and thin for niche AI titles.

Consistency with our own pages. AI and engineering ranges are aligned with the estimates already published in our fintech benchmark, AI jobs guide and role guides, so the same seat carries the same number across the site.

Limitations. Newer titles such as inference engineer, AI evaluation engineer and AI security engineer have the thinnest evidence, and their ranges carry the most uncertainty. Multipliers are indicative, and individual employers sit across them. Data cut-off 10 November 2026; next review November 2027. Our Intelligence section holds the related benchmarks, and senior quant and trading candidates can join the quant network.

Sources

If you are weighing an offer or a move, the ranges above are a starting point rather than an answer. Join our talent network and a partner who runs these searches will tell you where your profile sits. Explore open roles.