AI Field Engineer, EMEA
Fireworks AI18 days ago
Responsibilities
- Build end-to-end POCs, MVPs, and production integrations alongside customer engineering teams.
- Architect and size inference foundations for GenAI products and tune deployments for latency, throughput, cost, and scale.
- Deploy and validate model families using inference frameworks, selecting model shapes, quantization configurations, and serving patterns.
- Guide model selection, fine-tuning strategy, and evaluation methodology, and build fine-tuning and production-quality evaluation pipelines.
- Lead customer discovery, solution design, technical relationship management, and the path from initial engagement through production deployment.
- Work on-site with customers, aligning executives, ML engineers, and other stakeholders.
- Translate customer pain points, deployment patterns, failure modes, and feature gaps into product proposals, roadmap feedback, tooling, documentation, and platform improvements.
Requirements
- At least 5 years of experience in a hands-on, customer-facing technical role such as Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
- Demonstrated experience building and shipping production software within customer environments.
- Strong Python skills and familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of LLM inference, model serving, and fine-tuning workflows, including SFT; DPO and RFT are strong advantages.
- Experience with AWS, Azure, or GCP cloud infrastructure and deploying models on GPU infrastructure.
- Ability to lead discovery calls, present to vice presidents, and troubleshoot technical issues with ML engineers.
- Preferred qualifications include 10 or more years in technical field or engineering roles.
- Experience with vLLM, SGLang, or TensorRT-LLM; production-scale GenAI deployments; Azure AI Foundry, AWS Bedrock, AWS SageMaker, or GCP Vertex; and agentic systems or AI-native developer toolchains.
Benefits
- Work on cutting-edge AI infrastructure and model-serving challenges.
- Collaborate with world-class engineers and AI researchers.
- High ownership and direct impact in a fast-growing company with minimal bureaucracy.
- Customer-facing EMEA role involving on-site work with customers.