AI Field Engineer - AI Natives
Fireworks AI5 months ago
Base Salary
$200k - $260k/yr
Responsibilities
- Build end-to-end POCs, MVPs, and production integrations inside customer codebases and infrastructure.
- Architect inference foundations and size deployments for AI-native customer products.
- Run load tests and establish latency, throughput, and cost baselines against realistic traffic.
- Deploy and validate model families using inference frameworks and tune model shapes, quantization configurations, and serving patterns.
- 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, own the technical relationship through deployment, and collaborate directly with customer engineering teams on-site.
- Translate recurring customer pain points into product proposals, tooling, documentation, platform improvements, and roadmap feedback.
Requirements
- At least 5 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 production software with customers and ship code into another organization’s production environment.
- Strong Python skills and familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of inference trade-offs, model serving, and fine-tuning workflows, with SFT required and DPO/RFT preferred.
- Experience with AWS, Azure, or GCP and deploying models on GPU infrastructure.
- Ability to lead discovery calls, present to VP-level stakeholders, and debug technical issues with ML engineers.
- Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
- Preferred: 10+ years in technical field or engineering roles.
- Preferred: experience with vLLM, SGLang, or TensorRT-LLM and tuning deployments for real workloads.
- Preferred: experience with forward-deployed or embedded engineering organizations.
- Preferred: experience as a technical founder or early engineer at an AI-native company.
- Preferred: track record taking GenAI POCs through production-scale deployment.
- Preferred: experience with Azure AI Foundry, AWS Bedrock, AWS SageMaker, or GCP Vertex.
Benefits
- Work involves on-site customer engagements and embedded collaboration with customer engineering teams.
- Opportunity to work on frontier AI infrastructure, model serving, and production GenAI deployments.
- Collaborate with engineers and AI researchers in a fast-growing, inclusive environment.
- Equal-opportunity employer committed to diversity and inclusion.
Categories
Forward DeployedML Engineering
About Fireworks AI
Fireworks AI builds a generative AI platform for developers and enterprises to train, fine-tune, and serve open models for production use across text, image, audio, embeddings, and multimodal workloads. It offers managed inference and tooling via APIs on globally distributed infrastructure, with a usage-based SaaS model. Founded in 2022 and headquartered in San Mateo, CA, Fireworks AI is a privately held, Series D company.