Nanonets~3mo ago

Forward Deployed Engineer

India·Bangaloremid

Data ScienceOtherForward Deployed Engineer

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Quick Summary

Overview

About Nanonets Nanonets has a vision to help computers see the world starting with reading and understanding documents.Machine Learning (ML) is no longer a futuristic concept—it's a present-day powerhouse transforming the business landscape.

Requirements Summary

Experience building AI-native applications, including: chatbot / conversational interfaces, agentic workflows, RAG systems. Strong understanding of frontend system design, including: state management (local vs global vs server state), performance…

Technical Tools

machine-learningperformance-optimizationsystem-design

About Us:
Nanonets agents are built for complex business processes. Ranked #1 in understanding unstructured data and applying business rules in processes like accounts payable, order management, and supply chain.

Nanonets agents handle the exceptions other tools miss, reducing processing time by 94% and delivering clean data to SAP, Salesforce, or any system of record. That's why global enterprises reach for Nanonets when workflows are complex and accuracy is non-negotiable.

Learn more about us here:
Youtube
Hugging Face
Nanonets Research

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.

About the Role

~1 min read

This is a full-time, on-site role for a Forward Deployed Engineer based in Bangalore, India.

In this role, you will work directly with customers to design, build, and deploy AI-driven systems into live production environments. You will operate at the intersection of frontend, backend, and infrastructure, owning problems end-to-end — from initial requirements to production rollout. You will design AI-native interfaces and workflows, integrate LLM-powered systems, and build real-time applications that connect software to physical operations.

Requirements

~1 min read

Experience building AI-native applications, including: chatbot / conversational interfaces, agentic workflows, RAG systems.
Strong understanding of frontend system design, including: state management (local vs global vs server state), performance optimization, caching, and rendering patterns.
Solid understanding of backend and infrastructure systems, including APIs, data flow, authentication/authorization, and secure data handling — with the ability to debug, design, and collaborate effectively across these layers
Hands-on experience building production LLM systems, including RAG pipelines, agent orchestration, embeddings/vector search, and prompt design — with a strong understanding of trade-offs (latency, cost, hallucinations, reliability)
Ability to own problems and systems end-to-end, from first principles and problem definition through design, implementation, and production.
Strong foundations in computer science and software engineering principles
Experience working in client-facing or high-ownership environments is a plus
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)