Forward Deployed Engineer (FDE) – GenAI / LLM

INGENworksUnited States🇺🇸United StatesPosted Oct 6, 2026

Quick Overview

Seniority

Mid Senior

Work mode

Remote

Location

United States

Posted

Yesterday

DockerNode.jsAWSAzureGenerative AIGoogle CloudJavaKubernetesLLMPythonTypeScript

Forward Deployed Engineer (FDE) – GenAI / LLM
Location: Remote
Work Authorization: / / H1B
Experience: 8+ Years

Certification: Anthropic Certification – Mandatory

🔹 Roles & Responsibilities

Work directly with customers to understand business and technical requirements.
Design, prototype, integrate, and deploy AI/LLM-powered solutions.
Build rapid POCs and take solutions from concept → prototype → production.
Develop production-ready applications using Python, TypeScript, Node.js, Go, or Java.
Integrate LLMs, GenAI, APIs, SDKs, databases, cloud platforms, and enterprise systems.
Troubleshoot application, integration, and deployment issues.
Translate ambiguous customer requirements into scalable technical solutions.
Collaborate with Product, Engineering, Solutions, and customer teams.
Participate in technical workshops, architecture discussions, customer meetings, and demos.
Provide technical documentation and communicate recurring customer requirements to Product/Engineering.

🔹 Required Qualifications

8+ years of software engineering/application development experience.
Strong hands-on programming experience with Python, TypeScript, Node.js, Go, or Java.
Experience building and deploying production-grade applications.
Strong APIs, SDKs, integrations, and web services experience.
Hands-on Generative AI / LLM / AI application experience.
Experience with rapid prototyping, debugging, and problem-solving.
Strong customer-facing and technical stakeholder communication skills.
Ability to work independently in ambiguous, fast-paced environments.
Ability to translate customer problems into practical technical solutions.
Anthropic Certification – Mandatory.

🔹 Preferred Qualifications

Experience as an FDE, Solutions Engineer, Customer Engineer, Solutions Architect, or Full Stack Engineer.
Production experience with LLM-powered applications.
Experience with LLM APIs, Prompt Engineering, RAG, AI Agents/Agentic AI.
Cloud experience with AWS, Azure, or Google Cloud Platform.
Docker, Kubernetes, CI/CD, and DevOps experience.
Experience working with enterprise customers and complex production environments.