Remote AI Engineer: Lead End-to-End LLM Apps

Scalepex; United States; Remote; USD 90,000 - 150,000; Part time

Benefits offered by this job

100% Remote

Contractor scheme

Job summary

Scalepex is seeking a remote AI engineer to build foundational AI capabilities and lead end-to-end AI applications from prototype to production. You will collaborate with founders, clients, and engineers to shape technical and product direction, deploying LLM-based systems with RAG pipelines and fine-tuned models.

You’ll own the delivery, iterate rapidly, and operate with autonomy in a fast-changing environment, occasionally touching frontend or data pipelines as needed.

Qualifications

• Proven experience with LLMs, prompting, fine-tuning, and RAG.
• Strong Python engineering skills with modular codebase and clean practices.
• Experience deploying ML models to cloud environments (AWS/GCP) using Docker and production pipelines.

Responsibilities

• Build foundational AI capabilities and scalable products, with growth into team leadership.
• Lead design and development of end-to-end AI applications from prototype to production.
• Collaborate with founders, clients and engineers to shape technical and product direction.
• Design and deploy LLM-based systems, including RAG pipelines, fine-tuned models, and embedding search.
• Own delivery: architect, implement, test, and ship real-world solutions.
• Iterate rapidly, exploring new tools and approaches to solve problems creatively.
• Operate autonomously in fast-changing environments, sometimes as the sole engineer.
• Occasionally contribute to frontend, dev tooling, or data pipelines as needed.

Skills

LLMs

Prompting

Fine-tuning

RAG

Vector databases

Python

AWS

GCP

Docker

ML Pipelines

Startup mindset

Communication

Conversational AI

Voice AI

PyTorch

Scikit-learn

React

CI/CD

Tools

Docker

Job description

Scalepex is seeking a remote AI engineer to build foundational AI capabilities and lead end-to-end AI applications from prototype to production. You will collaborate with founders, clients, and engineers to shape technical and product direction, deploying LLM-based systems with RAG pipelines and fine-tuned models.

You’ll own the delivery, iterate rapidly, and operate with autonomy in a fast-changing environment, occasionally touching frontend or data pipelines as needed.