Full-Stack AI Engineer, Production LLMs & Infra

ramp; New York, California (NY, MO); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible PTO

Centralized home-office equipment

Health and wellness stipend

Budget for intra-office travel

Weekly coffee stipend

Job summary

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We hire people with high agency and urgency; at Ramp, everyone is a builder who owns problems end to end and makes consequential decisions.

The Applied AI team seeks strong full-stack engineers proficient in web frameworks, backend development and infrastructure. You will work on AI Agents, Retrieval-Augmented Generation, Structured Extraction, and LLM inference

Qualifications

• Proficiency in full-stack development with a strong understanding of web frameworks, backend systems and cloud infrastructure.
• Track record delivering production-grade AI projects involving LLMs and AI inference.
• Experience building backend systems and infrastructure to support AI-driven products.

Responsibilities

• Ship full-stack AI projects end to end
• Build and integrate components for AI infrastructure, supporting production-level inference and fine-tuning
• Develop and improve engineering processes, tools, and systems to scale AI solutions across Ramp
• Create tools and internal platforms to enhance productivity of Ramp's AI and engineering teams

Skills

Full-stack dev

LLM production use

Cloud infrastructure

Job description

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We hire people with high agency and urgency; at Ramp, everyone is a builder who owns problems end to end and makes consequential decisions.

The Applied AI team seeks strong full-stack engineers proficient in web frameworks, backend development and infrastructure. You will work on AI Agents, Retrieval-Augmented Generation, Structured Extraction, and LLM inference