Forward Deployed Engineer

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. Nanonets is at the forefront of this transformation, offering innovative ML solutions designed to make document related processes faster than ever before.

From automating data extraction processes to enhancing reconciliation, our solutions are designed to revolutionize workflows, optimize operations, and unlock untapped potential for our clients. Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data

We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital & YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.

Read about the release here: Forbes | TechCrunch

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

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.

Qualifications

• 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)