AI Field Engineer - Enterprise
Hybrid (New York, NY), Hybrid (Remote, USA), Hybrid (San Mateo, CA)$200k - $260k + equityfull-timePosted 4mo ago
About the role
AI Field Engineers embed with customers and partners to turn complex AI problems into production systems, combining hands-on technical delivery with executive-level stakeholder management in an enterprise GenAI context.
Responsibilities
- Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
- Architect inference foundations and size deployments for scalable market adoption.
- Run load tests, establish latency/throughput/cost baselines, and tune deployments to targets.
- Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns.
- Guide customers on model selection and fine-tuning strategy (SFT, DPO, RFT) and run fine-tuning pipelines with customers.
- Design and implement evaluation frameworks that measure production-quality metrics.
- Lead structured discovery conversations, manage executive relationships, and translate customer pain points into product improvements.
- Own the technical relationship from first engagement through production deployment, embedding with customer teams on-site.
Qualifications
- 5+ years in a hands-on, customer-facing technical role (Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder).
- Demonstrated ability to build production software with customers; shipped code in production environments.
- Strong Python skills; comfortable reading, writing, and debugging production code.
- Familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
- Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
- Exceptional communication: able to run discovery calls, present to VPs, and debug latency with ML engineers.
Skills
Required:PythonKubernetesLLM stackCloud platformsCommunication
Benefits
- Meaningful equity in a fast-growing startup.
- Competitive salary and comprehensive benefits package.
Last updated Jul 29, 2026. Interested? Apply on the company site.
About Fireworks AI
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