AI Field Engineer - Microsoft Foundry

About the role

At Fireworks, we're building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We've been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We're an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI. As an AI Field Engineer for Microsoft Foundry, you will be one of the technical owners of Fireworks' most strategic partnership. You'll work closely with Microsoft's field teams, Azure-aligned ISVs, and the SIs that run enterprise AI transformation programs to make Fireworks the default inference and fine-tuning layer in every Azure AI architecture your partners touch. The role sits at the intersection of engineering, partner development, and customer delivery. You build reference architectures, run benchmarks, debug production integrations, and co-develop POCs - all while holding your own in executive-level conversations about strategy, roadmap, and business outcomes. You spend most of your time building and enabling. You ship code, run joint POCs with Microsoft field teams, and architect deployments that span Azure Foundry and Fireworks. But you also lead discovery conversations, align partner stakeholders, and translate field signals into product improvements that compress the feedback loop from partner to roadmap. The Segment As a Field Engineer aligned with our Partnerships team you own the technical relationship between Fireworks and the Microsoft ecosystem, Azure field teams, ISVs building on Azure Foundry, and the SIs that deliver AI transformation programs on Azure. The Microsoft partnership is a core go-to-market bet: clients like UIPath, Stack Blitz, Motif run via Fireworks on Foundry.. Your job is to scale that pattern across the partner ecosystem. These engagements involve large, multi-stakeholder organizations, so you will need to navigate both the enterprise buyer (IT, security, compliance) and the builder (ML engineers, platform teams, app developers), while building the trusted-advisor relationships inside Microsoft's field that multiply your reach.

Responsibilities

• Technical Delivery and Deployment
• Be the technical lead on co-sell motions with Microsoft - joint reference architectures, Azure Foundry 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.
• Model Strategy and Fine-Tuning
• Guide Microsoft's 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.
• Product Feedback and Platform Improvement
• 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.

Requirements

• 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. You can explain why 50ms p99 matters to an enterprise CTO.
• 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. You know where Fireworks fits and where it doesn't.
• Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency iss

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