Senior Full Stack Engineer
NanoNets
Job description
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.
What we expect from you :
- 5-8 years of hands-on experience in full stack engineering.
- Experience working in a fast-moving startup, with a track record of shipping products quickly.
- Proficiency in at least one backend language (Go or Python) and one frontend framework (preferably React + TypeScript).
- Experience with using LLM APIs and LLM-based applications.
- Strong understanding of web architecture, distributed systems, APIs, and relational databases.
- Ability to write clean, testable code and solve production issues effectively.
- A builder’s mindset: ownership, initiative, and bias for action.
Our Tech Stack :
Backend: Go, Python
Frontend: React, TypeScript
Databases & Infra: PostgreSQL, Redis, AWS/GCP
Why join us ?
- Work on cutting-edge AI agents transforming the healthcare industry.
- Be part of a small, high-impact, no-bureaucracy team.
- Ship products that make a real-world difference for customers.
- Learn fast, grow fast - with competitive compensation & career growth opportunities.
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
