AI Field Engineer - Strategic Partnerships
Hybrid (New York, NY), Remote, Hybrid (San Mateo, CA)$200k - $260k + equityfull-timePosted 4mo ago
About the role
AI Field Engineer role focused on strategic partnerships, owning technical relationships with partner ecosystems, delivering technical deployments, POCs, and product feedback to accelerate Fireworks adoption within partner architectures.
Responsibilities
- Be the technical lead on co-sell motions with Strategic Partners — joint reference architectures, partner integration patterns, and shared POCs for strategic accounts.
- Build end-to-end POCs and MVPs alongside partner engineering teams, working inside their codebases, infrastructure, and constraints.
- Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets.
- Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
- Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
- Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
- Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores
- Own the feedback loop — surface partner-driven product gaps to Fireworks engineering, and translate the roadmap back into partner messaging.
- Ship external technical content: reference architectures, integration guides, and benchmark posts that make it easy for partners to win deals with us.
- Track pipeline health; flag risks and opportunities to Field leadership weekly
Qualifications
- 3+ years in a pre-sales, partner engineering, forward-deployed, or technical consulting role.
- 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.
- Hands-on fluency with LLM inference: latency/throughput tradeoffs, batching strategies, quantization, structured outputs, function calling.
- Real experience with fine-tuning — LoRA at minimum, RFT a strong plus. You understand when SFT is enough and when it isn't.
- Deep familiarity with the Azure AI stack: Azure Foundry, Azure OpenAI Service, Azure ML, AKS, Entra/RBAC for AI workloads.
- 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.
Skills
Required:PythonKubernetesLLM inferenceFine-tuningAzure AI stackCommunication
Last updated Jul 29, 2026. Interested? Apply on the company site.
About Fireworks AI
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