The median salary at Nanonets in India is ₹31.9L per year, with most roles between ₹29.1L and ₹33.8L CTC. Below is Nanonets's pay broken down by role and experience, aggregated from 50 employee-reported salary reports.
Average annual CTC for each role reported at Nanonets, highest first.
| Role | Experience | Avg CTC | Typical range |
|---|---|---|---|
| Engineering Manager | 10–11 yrs | ₹61.8L | ₹58.7L–₹64.9L |
| Customer Success Manager | 8–11 yrs | ₹53.6L | ₹50.9L–₹56.2L |
| Senior Front end Developer | 7–7 yrs | ₹47.4L | ₹45.0L–₹49.8L |
| Product Manager | 1–8 yrs | ₹43.0L | ₹40.9L–₹45.1L |
| Full Stack Engineer | 4–8 yrs | ₹42.3L | ₹40.2L–₹44.5L |
| People Head | 7–8 yrs | ₹41.2L | ₹39.1L–₹43.3L |
| Marketing Manager | 7–12 yrs | ₹40.0L | ₹38.0L–₹42.0L |
| Lead Product Analyst | 2–4 yrs | ₹34.0L | ₹32.3L–₹35.7L |
| SDE | 2–2 yrs | ₹33.5L | ₹31.8L–₹35.1L |
| Software Engineer | 0–5 yrs | ₹32.9L | ₹26.4L–₹39.5L |
| Software Development Engineer | 3–3 yrs | ₹30.9L | ₹29.4L–₹32.5L |
| Software Developer | 1–4 yrs | ₹30.4L | ₹28.8L–₹31.9L |
| Senior Business Analyst | 3–5 yrs | ₹28.3L | ₹26.9L–₹29.7L |
| QA Lead | 8–8 yrs | ₹27.8L | ₹26.4L–₹29.2L |
| Deep Learning Engineer | 2–3 yrs | ₹25.0L | ₹23.8L–₹26.3L |
| Product Marketing Associate | 1–2 yrs | ₹23.7L | ₹22.5L–₹24.9L |
| Business Analyst | 1–2 yrs | ₹20.9L | ₹19.8L–₹21.9L |
| Content Writer | 5–5 yrs | ₹20.6L | ₹19.6L–₹21.6L |
| Content Lead | 5–5 yrs | ₹17.0L | ₹16.1L–₹17.8L |
| Delivery Lead | 4–6 yrs | ₹15.1L | ₹12.8L–₹17.4L |
Nanonets has 16 open roles live on HireHire right now. Explore Nanonets's current openings, culture and team.
The median salary at Nanonets is around ₹31.9L per year (CTC), with most roles falling between ₹29.1L and ₹33.8L. Figures are aggregated from 50 employee-reported salary reports across 20 roles.
Among reported roles, Engineering Manager is the highest-paid at Nanonets, averaging about ₹61.8L per year.
Early-career roles at Nanonets start around ₹20.9L per year, rising with experience and specialisation.
They are median estimates from crowdsourced, employee-reported data (AmbitionBox) and are indicative, not guarantees. Actual offers vary by role, location, skills and negotiation.