AI Field Engineer - Strategic Partnerships

Stack

Responsibilities

• ▹Act as technical lead on co-sell motions with Strategic Partners, building joint reference architectures and shared POCs
• ▹Build end-to-end POCs and MVPs with partner engineering teams inside their own codebases and infrastructure
• ▹Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles
• ▹Deploy and validate new model families on inference frameworks (vLLM, SGLang), tuning shapes and serving patterns
• ▹Guide customers on model selection and fine-tuning strategy (SFT, DPO, RFT)
• ▹Build and run fine-tuning pipelines directly with customers
• ▹Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores
• ▹Own the feedback loop between partner ecosystems and Fireworks engineering
• ▹Ship external technical content such as reference architectures, integration guides, and benchmark posts
• ▹Track pipeline health weekly and flag risks and opportunities to Field leadership

Requirements

• ▹3+ years in pre-sales, partner engineering, forward-deployed, or technical consulting roles
• ▹Demonstrated ability to build production software with customers, not just advise on it
• ▹Strong Python skills, comfortable reading, writing, and debugging production code
• ▹Familiarity with Kubernetes and infrastructure engineering
• ▹Hands-on fluency with LLM inference: latency/throughput tradeoffs, batching, quantization, structured outputs, function calling
• ▹Real fine-tuning experience (LoRA at minimum, RFT a strong plus)
• ▹Deep familiarity with the Azure AI stack (Azure Foundry, Azure OpenAI Service, Azure ML, AKS, Entra/RBAC)
• ▹Exceptional communication across executive and engineering levels

Nice to have

• ▹5+ years owning a technical relationship with a hyperscaler or major SI, not just supporting one
• ▹Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM)
• ▹Prior role at a hyperscaler, AI-native cloud, or inference provider
• ▹Deep familiarity with other strategic partner stacks
• ▹Experience with agentic frameworks (LangChain, LlamaIndex, custom tool-use pipelines)
• ▹Background in model evaluation and awareness of benchmark gaming risks
• ▹Published technical blog posts or reference architectures
• ▹Track record taking GenAI POCs from prototype to production-scale deployments

Soft skills

What we offer

• ▹$200,000-$260,000 on-target earnings plus equity
• ▹Meaningful equity in a fast-growing startup
• ▹Competitive salary and comprehensive benefits package

About the company

Fireworks is building the future of generative AI infrastructure, delivering one of the industry's fastest and most scalable inference platforms. A Series C company valued at $4 billion, backed by investors including Benchmark, Sequoia, Lightspeed, and Index, and founded by veterans of Meta PyTorch and Google Vertex AI.