Remote AI/ML Engineer — LLMs, RAG & Secure Cloud AI

YO AI Labs; Houston (TX); Remote; USD 120,000 - 190,000; Full time

Job summary

YO AI Labs seeks an experienced AI/ML Engineer to build secure, scalable AI solutions using LLMs, RAG, prompt engineering, and multi-agent systems. You will work across cloud AI platforms and contribute to proprietary infrastructure.

You will design data pipelines, REST APIs, and SDKs while collaborating with security and product teams to deliver production‑grade systems with modern DevOps practices.

Qualifications

• Proficient in Python for AI/ML development and production-grade APIs.
• Hands-on experience with LLMs, RAG, and prompt engineering.
• Experience designing multi-agent systems and tool orchestration.
• Familiar with cloud AI services including GovCloud platforms and Vertex AI.

Responsibilities

• Design, build, and deploy secure, scalable AI/ML solutions.
• Develop multi-agent systems using LangGraph and LangChain.
• Deploy AI solutions across secure cloud environments (GovCloud, Vertex AI, Bedrock).
• Build ETL data pipelines, metadata catalogs, and ontologies for training and inference.
• Develop and maintain REST APIs and SDK integrations.
• Collaborate with product, security, and engineering teams to ensure secure, scalable solutions.
• Follow secure coding, DevOps, and CI/CD practices.
• Document decisions and communicate complex concepts to technical and non-technical stakeholders.

Skills

Python

LLMs

RAG

prompt engineering

multi-agent orchestration

REST APIs

CI/CD

communication

Tools

LangGraph

LangChain

AWS GovCloud

Google GovCloud

Azure IL5+

Vertex AI

AWS Bedrock

Job description

YO AI Labs seeks an experienced AI/ML Engineer to build secure, scalable AI solutions using LLMs, RAG, prompt engineering, and multi-agent systems. You will work across cloud AI platforms and contribute to proprietary infrastructure.

You will design data pipelines, REST APIs, and SDKs while collaborating with security and product teams to deliver production‑grade systems with modern DevOps practices.