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Fireworks is a Series D AI platform company (valued at $17.5B) that enables enterprises to build, train, and serve specialized AI models tailored to their data and workflows. Backed by NVIDIA, Sequoia, Benchmark, and others, Fireworks powers production AI across text, image, embedding, audio, and multimodal workloads.
As an AI Field Engineer in the AI Native segment, you will be the technical tip of the spear, embedding directly with Fireworks' most ambitious AI-native customers—companies where GenAI is the core product, not a feature. This is a hands-on-keyboard role that sits at the intersection of engineering, product, and customer delivery.
You will spend most of your time building: shipping code, running benchmarks, debugging production issues, and architecting deployments. You'll build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases and infrastructure. You'll architect inference foundations for customers whose core product depends on GenAI, size deployments to prevent infrastructure from becoming a bottleneck, and run load tests to establish latency, throughput, and cost baselines against realistic traffic profiles.
On the model strategy side, you'll guide customers on model selection, fine-tuning approaches (SFT, DPO, RFT), and evaluation methodology. You'll build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets. You'll design evaluation frameworks that measure production-quality metrics, not just benchmark scores.
You'll also lead structured discovery conversations to unpack customer pain points and constraints before proposing solutions. You'll own the technical relationship from first engagement through production deployment, embedding with their engineering team as a peer. Credibility comes from what you build alongside them. You'll spend significant time on-site with customers, building trust and momentum in person.
Finally, you'll identify recurring customer pain points and translate them into concrete product proposals, working directly with Fireworks' engineering and product teams. You'll codify repeatable deployment patterns and contribute them back to internal tooling and the platform itself, feeding customer signals into the product roadmap with specificity and urgency.
This role requires 5+ years of hands-on experience, ideally with production ML systems, inference optimization, or customer-facing technical delivery at high-growth companies.
