AI Field Engineer – Enterprise (Remote U.S.)

NEPSE Trading; United States; A distancia; USD 176.000 - 224.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Visa sponsorship

Equity

Descripción de la vacante

NEPSE Trading is seeking an AI Field Engineer (Enterprise) for remote work in the United States with 3+ years of hands-on GenAI experience. You will embed with large enterprise customers to turn complex AI challenges into production systems, balancing technical execution with executive engagement.

You will lead discovery calls, scope POCs, and build end-to-end production integrations within customer environments while navigating security and infrastructure constraints.

Formación

• 3+ years of hands-on AI engineering experience with GenAI workloads.
• Experience with LLM inference and/or training.
• Proficiency in Python and production deployments in customer environments.
• Familiarity with open-model frameworks (vLLM, SGLang, TensorRT-LLM).
• Experience with fine-tuning workflows: SFT required; DPO/RFT preferred.

Responsabilidades

• Lead discovery calls, scope POCs, and run load tests to validate architecture.
• Build end-to-end POCs and production integrations inside customer environments.
• Advise on model selection and fine-tuning strategies for production at scale.
• Manage relationships with enterprise stakeholders and drive project momentum.
• Provide deployment insights back to engineering to guide product direction.

Conocimientos

LLM inference

Python

Cloud platforms

Kubernetes

Open-model frameworks

Fine-tuning workflows

Production deployment

Executive communication

Herramientas

vLLM

SGLang

TensorRT-LLM

Kubernetes

AWS

Azure

GCP

Descripción del empleo

AI Field Engineer – Enterprise Full-Time | Remote (U.S.)

Compensation: $176,000 – $224,000 Base On-Target Earnings (OTE): $220,000 – $280,000 + Meaningful Equity

About the Role

We are looking for an AI Field Engineer (Enterprise) with 3+ years of experience to embed with ambitious enterprise customers and turn complex GenAI challenges into production systems—fast. You'll combine deep hands‑on engineering with the executive presence to earn trust across large organizations and help drive engagements from initial technical discovery through production deployment.

What You’ll Do

Lead technical discovery calls, scope proof‑of‑concepts, and run load tests and evaluations to validate the right model architecture and deployment configuration for enterprise customers. Build end‑to‑end POCs and production integrations directly inside customer environments while navigating infrastructure, security requirements, and organizational constraints. Guide customers on model selection, fine‑tuning strategies (SFT, DPO, RFT), and evaluation frameworks to move from experimentation to production at scale. Manage relationships across multiple enterprise stakeholders, identifying technical champions and helping align teams to move projects forward efficiently. Provide recurring customer feedback and deployment insights to the engineering organization to help shape future product development.

Required Qualifications

• Deep hands‑on experience with LLM inference and/or training.
• Working knowledge of open‑model frameworks such as: vLLM, SGLang, TensorRT-LLM.
• Experience with fine‑tuning workflows: SFT required; DPO and/or RFT strongly preferred.
• Candidates whose experience is limited to closed‑model API integrations alone will not be a fit.
• Proven ability to build and deploy production code within customer environments, including POCs or MVPs running in production.
• Strong Python programming skills.
• Experience with GPU infrastructure.
• Experience using AWS, Azure, or GCP.
• Experience with Kubernetes.
• Strong communication skills with the ability to engage both technical and executive audiences.
• Customer‑facing engineering experience in roles such as: Field Engineer, Applied AI Engineer, Solutions Architect, AI Infrastructure Engineer, ML Engineer, Software Engineer with pre‑sales exposure.
• 3+ years of relevant experience.

Preferred Qualifications

• Experience with DPO or reinforcement fine‑tuning (RFT).
• Experience deploying enterprise‑scale GenAI applications.
• Experience working directly with production AI infrastructure.
• Interest in contributing to product direction based on customer feedback.
• Comfortable working in fast‑paced, high‑growth environments with significant ownership.

Technical Environment

• Python
• vLLM
• SGLang
• TensorRT-LLM
• Kubernetes
• AWS, Azure, GCP
• Azure AI Foundry
• AWS Bedrock
• AWS SageMaker
• GCP Vertex AI
• GPU Infrastructure
• Open‑source LLM Frameworks
• LLM Fine‑Tuning (SFT, DPO, RFT)

Compensation & Benefits

Base Salary: $176,000 – $224,000 On‑Target Earnings: $220,000 – $280,000 (80/20 base/variable split)

• Quarterly variable compensation based on individual and team performance.
• Meaningful equity package.
• Visa sponsorship is available. H-1B transfers TN visas O-1 visas considered on a case‑by‑case basis.

Location

Remote (United States). Employees located near company hubs may follow a hybrid schedule. Regular travel to enterprise customer sites is expected.

About the Company

This fast‑growing AI infrastructure company helps organizations build, fine‑tune, and scale production AI applications using open‑source models. Its platform is designed to deliver high‑performance inference, lower latency, and greater scalability for enterprise AI workloads. Founded in 2021, the company has grown to approximately 211 employees and has raised over $327 million in funding. The engineering culture emphasizes technical excellence, ownership, rapid execution, and close collaboration between customer‑facing teams and product engineering. The organization values engineers who enjoy solving complex technical challenges, working directly with customers, and helping shape the future of AI infrastructure.

Originally posted on Himalayas