AI Field Engineer / Forward Deployed Engineer (FDE)

Qureos•New York, NY

5d•Remote

About The Position

We’re hiring an AI Field Engineer / Forward Deployed Engineer (FDE) to join our AI’s high-velocity team. You’ll work directly with ambitious AI-native companies to turn complex AI challenges into production-ready systems. This is a highly hands-on role sitting at the intersection of AI engineering, product, and customer delivery. You’ll build POCs, MVPs, and production integrations while working directly with customers, account executives, and engineering teams. You’ll also engage with technical and executive stakeholders to discuss architecture, strategy, and business outcomes. This is not a traditional consulting or solutions role; you’ll be hands-on-keyboard, writing code, deploying systems, solving technical problems, and contributing directly to our products and platform.

Requirements

3–10 years of experience in a client-facing technical or AI/ML engineering role.
Strong Python programming skills.
Experience building and deploying AI/ML or generative AI applications.
Experience working with LLMs and/or open-source AI models.
Ability to work directly with customers and communicate technical concepts clearly.
Experience building POCs and taking solutions toward production.
Strong problem-solving skills and the ability to operate effectively in ambiguous environments.
Willingness to work hands-on across engineering, customer delivery, and product.

Nice To Haves

Experience with vLLM
Experience with SGLang
Experience with TensorRT-LLM
Experience with Kubernetes
Experience with AWS, Azure, or GCP
Experience with AWS Bedrock / SageMaker
Experience with Azure AI Foundry
Experience with GCP Vertex AI
Experience with LLM fine-tuning, including SFT, DPO, or RFT
Experience with GPU infrastructure
Experience with Model inference and optimization

Responsibilities

Work directly with customers to understand their technical and business challenges.
Design and build POCs, MVPs, and production AI applications.
Deploy and optimize LLM and generative AI workloads in production.
Work with open-source models, inference infrastructure, and AI/ML platforms.
Collaborate with customer engineering teams, account executives, and Fireworks product/engineering teams.
Translate customer requirements into scalable technical solutions.
Troubleshoot complex AI, infrastructure, and deployment challenges.
Communicate technical architecture and tradeoffs to both engineers and executive stakeholders.
Contribute code and product improvements directly to the codebase.
Turn customer learnings into product feedback and help shape our roadmap.
Take ownership of projects from initial discovery through production deployment.