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AI Field Engineer - Enterprise

Engineering · Posted 3 months ago

We are looking for an AI Field Engineer (Enterprise) with 3+ years of experience to embed with Fireworks AI's most ambitious enterprise customers and turn complex GenAI challenges into production systems — fast. You'll be the technical tip of the spear, pairing deep hands-on engineering with the executive presence to e...

Way of working
Remote
Location
San Mateo, CA, New York, NY
Pay range
$220,000 to $280,000
Level
Mid
Experience
3+ years
Type
Full time
Visa sponsorship
Not offered for this role
The company
Software Development · 200 to 1000 people

Skills that matter here

PythonvLLMSGLangTensorRT-LLMKubernetesAWSAzureGCPAzure AI FoundryAWS BedrockAWS SageMakerGCP Vertex AILLM Fine-Tuning (SFT, DPO, RFT)GPU InfrastructureOpen-source LLM frameworks

The full description

We are looking for an AI Field Engineer (Enterprise) with 3+ years of experience to embed with Fireworks AI's most ambitious enterprise customers and turn complex GenAI challenges into production systems — fast. You'll be the technical tip of the spear, pairing deep hands-on engineering with the executive presence to earn trust across large organizations and drive deals from first discovery call to production deployment.

What will you be doing?

- Lead technical discovery calls, scope POCs, and run load tests and evaluations to validate the right model architecture and deployment configuration for each enterprise customer

- Build end-to-end POCs and production integrations hands-on-keyboard inside customer environments, navigating their infrastructure, security requirements, and organizational constraints

- Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation frameworks — moving them from open-model exploration to production at scale

- Manage multi-stakeholder enterprise relationships — identifying technical champions, navigating org politics, and aligning the right people to move deals forward quickly

- Feed recurring customer pain points and deployment patterns back into the product roadmap, acting as a direct feedback loop between the field and engineering

Key Requirements

- Deep hands-on experience with LLM inference and/or training — working knowledge of open-model frameworks (vLLM, SGLang, TensorRT-LLM) and fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus); candidates with only closed-model/API-wrapper experience will not clear the bar

- Proven ability to ship production code inside a customer's environment — not just advisory work; you've built and deployed POCs/MVPs that ran in someone else's prod system

- Strong Python skills plus GPU/cloud infrastructure experience (AWS, Azure, or GCP) and comfort with Kubernetes

- Executive presence and enterprise navigation skills — able to run a technical deep-dive with an ML engineer and present architecture trade-offs to a VP in the same afternoon

- Pre-sales or customer-facing field engineering experience (FDE, Applied AI Engineer, Solutions Architect, or similar); pure software engineers without customer-facing exposure are not a fit

How hiring runs

  1. 1Take-Home Assignment
  2. 2Recruiter Screen
  3. 3Culture + Live Coding
  4. 4Discovery + Hiring Manager
  5. 5On-Site Final Loop
  6. 6Executive Interview

Interested in this one?

There is no apply button here on purpose. Tell us about yourself, we book a short call, and if this role fits we walk you through the company and ask before anything is sent. Always free for you.

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