Forward Deployed Engineer

• Work directly with customers to design and deploy AI-driven systems into live production environments
• Design AI-native interfaces and workflows for complex business processes
• Integrate LLM-powered systems and build real-time applications
• Own problems end-to-end from requirements gathering through production rollout
• Build and optimize RAG pipelines, agent orchestration, and vector search systems
• Debug and collaborate across frontend, backend, and infrastructure layers
• Handle production LLM system challenges including latency, cost, hallucinations, and reliability

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.

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 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

• 2+ years as a Forward Deployed Engineer, software engineer, ML engineer or equivalent — startup experience preferred; founder or founding engineer background is a plus.

• 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)

Sourced from the fund's portfolio job board — apply on the company's site.