Senior Forward Deployed Software Engineer (FDSE) with GenAI

Quick Facts

• Role: Senior Forward Deployed Software Engineer (FDSE) with GenAI

• Focus: Customer-embedded delivery of production-ready, LLM-enabled applications

• Travel: Up to 30% onsite

Description

Own end-to-end delivery of LLM-enabled applications in agile sprints while embedded with strategic enterprise customers. Lead full-stack technical architecture and implementation decisions, integrating backend services, data orchestration, LLM pipelines, vector search, and front-end UI. Convert engagements into reusable libraries, SDKs, prompts, scaffolds, and documentation to accelerate future deployments and inform the platform roadmap.

Responsibilities

• Build production-ready GenAI solutions: backend services, data orchestration, LLM pipelines, and front-end integrations

• Diagnose customer issues, identify high-value AI opportunities, and adapt deployments in live environments

• Act as the “CTO of the build” by making architecture/implementation decisions

• Engineer across the full stack: APIs (REST/GraphQL), orchestration pipelines, vector database integrations, LLM frameworks (LangChain, Semantic Kernel), and UI components (React, Angular)

• Integrate with legacy systems and deliver reliably and securely in ambiguous environments

• Codify reusable assets: libraries, SDKs, prompts, scaffolds, and documentation

• Influence platform and product with field-tested insights for the Now AI Platform

• Ensure performance, reliability, and security using debugging, latency tuning, and monitoring/observability

• Deploy and operate in cloud environments using CI/CD, containers, and infrastructure-as-code

• Provide engineering leadership for zero-to-one implementations and scalable long-term solutions

Requirements

• 10+ years of software engineering experience; at least 2 years in customer-facing or embedded roles

• Backend development experience with Python or Node.js or Java

• Frontend experience with React or Angular

• Hands-on experience with LLM tooling and patterns: prompt chaining, vector search, context management

• Experience with REST/GraphQL APIs, orchestration pipelines, and integrations with vector databases and LLM frameworks

• Cloud and DevOps fluency: CI/CD, containers, and infrastructure-as-code on AWS, Azure, or GCP

• Ability to design for performance, reliability, and security in distributed systems

• Strong communication with customer stakeholders; fluent English

• Willingness to travel up to 30%

Benefits

• Lead complex, high-impact AI projects with strategic enterprise customers and shape product/platform direction

• Full-stack work that advances practical, production-grade GenAI deployments and reusable engineering assets

• Travel allowance for onsite engagements and support for remote and on-site work as required