AI Field Engineer - Enterprise

Transparent Search Group · San Mateo, California, United States · 2 weeks ago

Work mode: Remote
Employment: Full time
Category: Industrial engineering
Experience: 3+ years

ai aws azure cloud fine-tuning gcp generative-ai kubernetes llm machine-learning notion

Company: Fireworks AI
Location: US-based, remote-friendly (offices in San Mateo, CA and New York, NY); regular travel to enterprise customers
Compensation: $176,000 - $224,000 base (OTE $220,000 - $280,000) + competitive equity
Employment Type: Full-time
Visa Sponsorship: H-1B transfers and TN; O-1 case by case

About Fireworks AI

Fireworks AI is a generative AI inference and fine-tuning platform that runs production workloads for companies including Uber, DoorDash, Notion and Cursor. It was founded by veterans of Meta's PyTorch team and Google Vertex AI.

Founded in 2021, Fireworks has about 200 people, has surpassed $1B in ARR and raised a Series D in 2026 at a $17.5B valuation, backed by Index Ventures, TCV and NVIDIA among others.

The Role

Fireworks AI is hiring AI Field Engineers (3+ years) to embed with its most ambitious enterprise customers and turn complex generative AI challenges into production systems, fast. You will be the technical tip of the spear, pairing deep hands-on engineering with the executive presence to earn trust across large organizations and carry deals from first discovery call to production deployment.

What You Will Do

Lead technical discovery, scope POCs, and run load tests and evaluations to choose the right model architecture and deployment configuration.

Build end-to-end POCs and production integrations hands-on inside customer environments, working within their infrastructure, security and organizational constraints.

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

Manage multi-stakeholder enterprise relationships: find technical champions and align the right people to move deals forward.

Feed recurring customer pain points and deployment patterns back into the product roadmap.

What You Bring

3+ years in client-facing AI/ML roles (forward deployed, solutions architect, applied AI, sales or customer engineering)

Shipped AI/ML production code inside a customer's environment, not only advisory work

Deep hands-on LLM inference and fine-tuning: open-model serving frameworks (vLLM, SGLang, TensorRT-LLM) and SFT at minimum

Owned the pre-sales field cycle end to end: discovery, POC scoping, evals and model selection

Strong Python plus GPU/cloud infrastructure (AWS, Azure or GCP) and Kubernetes

Experience at an AI-native or AI-infrastructure startup, or building AI features in enterprise SaaS

Executive presence with enterprise customers; willing to travel domestically

Nice to Have

DPO or RFT fine-tuning experience

Hyperscaler AI experience (Bedrock, SageMaker, Vertex AI, Azure AI Foundry)

Navigating enterprise organizations end to end

Interview Process

Take-home assignment, recruiter screen (30 min), culture and live coding (1 hour), discovery and hiring manager (45 min), on-site final loop (about 2 hours), executive interview (30 min).

Tech Stack

Python, vLLM, SGLang, TensorRT-LLM, Kubernetes, AWS, Azure, GCP, Bedrock, SageMaker, Vertex AI, LLM fine-tuning (SFT, DPO, RFT), GPU infrastructure

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