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Nanonets has a vision to help computers see the world starting with reading and understanding documents. Our product helps businesses automate document related workflows for enterprise office teams such as invoice data entry for AP teams, KYC automation for banks and insurance etc. Backed by $40M+ in total funding including our recent $29M Series B from Accel, alongside Elevation Capital and Y Combinator, we're scaling our deep learning capabilities to serve enterprise clients including Toyota, Boston Scientific, and Bill.com. You'll work on genuinely challenging problems at the intersection of computer vision, NLP, and generative AI. Nanonets is proud to be an equal opportunity workplace dedicated to pursuing, hiring, and retaining a diverse workforce. About the Role As a Senior fullstack engineer, you should be comfortable with both backend (Preferably Golang) and frontend (Preferably React). You will be primarily working on architecting and shipping new backend features like new integrations, enabling more machine learning API’s, building complex workflows & various growth hacking efforts. You will also work on optimizing response times, building features that will scale to 100’s of millions of documents we process every month. What we expect from you Agility in shipping features Good at code design and architecture Great communication Backend experience - Preferably golang, python Databases - Understanding of data modeling for Nosql preferably cassandra. Strong fundamentals in OOP design patterns. Basic understanding of Devops. Curiosity and Willingness to learn new things while solving a challenging problem. Learning and incorporating best practices in software development, security and design/architecture. Some of the interesting features we have shipped in backend Compile python code into C which could be imported into golang and then shipped as binary for on premise systems Autoscale GPU dependent services with kubernetes with a custom metric Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases Process large number of files in highly distributed manner in golang Intelligent lookups leveraging vector databases with data synced from ERP Systems Some of the interesting things we have shipped in frontend - Ability for users to annotate documents so AI can learn which fields to extract. Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Letting users build complex visual workflows around our API in our product. Let users visualize complex ML metrics in a very simple and intuitive way
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.