AI Field Engineer (Strategic Partnerships)

Join Fireworks as an AI Field Engineer for Strategic Partnerships. In this role, you will be the technical owner of Fireworks' most strategic partnership, working closely with field teams, ISVs, and SIs to make Fireworks the default inference and fine-tuning layer in every Partner AI architecture. You will build reference architectures, run benchmarks, debug production integrations, and co-develop POCs, while also engaging in executive-level conversations about strategy, roadmap, and business outcomes.

• Establish and maintain technical relationships with strategic partners, ensuring Fireworks is integrated into their AI architectures.
• Lead the technical delivery and deployment of co-sell motions with strategic partners, including building end-to-end POCs and MVPs.
• Provide feedback to Fireworks engineering based on partner-driven product gaps, and contribute to the development of external technical content.

• Real experience with fine-tuning — LoRA at minimum, RFT a strong plus. You understand when SFT is enough and when it isn't
• Hands-on fluency with LLM inference: latency/throughput tradeoffs, batching strategies, quantization, structured outputs, function calling. You can explain why 50ms p99 matters to an enterprise CTO
• Deep familiarity with the Azure AI stack: Azure Foundry, Azure OpenAI Service, Azure ML, AKS, Entra/RBAC for AI workloads. You know where Fireworks fits and where it doesn't
• Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering
• 3+ years in a pre-sales, partner engineering, forward-deployed, or technical consulting role
• 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
• Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment
• Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads
• 5+ years in technical field or engineering roles where you've owned a technical relationship with a hyperscaler or major SI, not just supported one
• Prior role at a hyperscaler, AI-native cloud, or inference provider
• Experience with agentic frameworks (LangChain, LlamaIndex, or custom tool-use pipelines) — you understand how inference latency and reliability shapes agent behavior at scale
• Deep familiarity with other strategic partner stacks: Platforms for AI workloads, network, and identity integration patterns. You know where Fireworks fits and where it doesn't
• Background in model evaluation — you understand why benchmark gaming is rampant and what rigorous evals actually look like
• You've written a technical blog post or reference architecture that people actually read
• Track record taking GenAI POCs from prototype to production-scale deployments