Fireworks AI - AI Field Engineer - Enterprise

• 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder. • Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment. • Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering. • Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus). • Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure. • Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon. • 10+ years in technical field or engineering roles. • Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads. • Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems. • Track record taking GenAI POCs from prototype to production-scale deployments. • Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex). • Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains. • Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted. • On Target Earnings (Plus Equity) • $200,000—$260,000 USD