AI Field Engineer - AI Natives

2 months ago

San Mateo, CA, USA or New York, NY, USASenior

H1B Sponsor

Base Salary

$200k - $260k/yr

Responsibilities

Build end-to-end POCs, MVPs, and production integrations alongside customer engineering teams within their codebases and infrastructure.
Architect and size inference foundations for GenAI products so deployments can scale without infrastructure bottlenecks.
Run load tests, establish latency, throughput, and cost baselines, and tune deployments against realistic customer traffic.
Deploy and validate model families on inference frameworks while selecting serving patterns, model shapes, and quantization configurations.
Advise customers on model selection, fine-tuning strategy, and evaluation methodology.
Build fine-tuning pipelines and evaluation frameworks that measure production-quality metrics.
Lead discovery conversations, own technical relationships through production deployment, and embed with customer engineering teams on-site.
Translate recurring customer pain points and deployment patterns into product proposals, internal tooling, documentation, and roadmap feedback.

At least five years of hands-on, customer-facing technical experience in roles such as Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build and ship production software in customer environments rather than only provide technical advice.
Strong Python skills, including reading, writing, and debugging production code.
Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of LLM inference trade-offs, model serving, and fine-tuning workflows, with SFT required at minimum and DPO/RFT as strong pluses.
Experience with AWS, Azure, or GCP cloud infrastructure and deploying models on GPU infrastructure.
Ability to lead discovery calls, present to executives, and troubleshoot technical issues with ML engineers.
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Preferred: ten or more years in technical field or engineering roles.
Preferred: experience with vLLM, SGLang, or TensorRT-LLM and tuning inference deployments for real workloads.
Preferred: experience in forward-deployed or embedded engineering organizations, as a technical founder or early AI-native engineer, or taking GenAI POCs to production scale.
Preferred: experience with Azure AI Foundry, AWS Bedrock or SageMaker, or GCP Vertex.

Work on cutting-edge AI infrastructure and model-serving challenges.
Collaborate with world-class engineers and AI researchers in a fast-growing environment.
The role includes on-site customer engagement and embedded work with customer teams.
Fireworks is an equal-opportunity employer committed to an inclusive workplace.