AI/ML Engineer - Secure GovCloud & LLMs (Remote)

YO AI Labs; Seattle (WA); Remote; USD 120,000 - 160,000; Full time

Job summary

YO AI Labs seeks an experienced AI/ML Engineer to design, build, and deploy secure, scalable AI systems. You will work with LLMs, RAG, prompt engineering, and multi-agent architectures to create production-grade ML applications. Strong cloud deployment experience and a focus on secure coding are required.

The role emphasizes collaboration with product and security teams, REST API and SDK integration, and ongoing documentation of technical decisions. Remote work is supported.

Qualifications

• Strong Python proficiency for AI/ML development and REST APIs.

Responsibilities

• Design, implement, and optimize AI/ML solutions using LLMs, RAG, and prompt engineering.
• Develop and orchestrate multi-agent systems using LangGraph and LangChain.
• Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust ETL and data pipelines, metadata catalogs, and ontologies for AI training and inference.
• Develop and maintain REST APIs and SDK integrations.
• Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.
• Follow modern secure coding, DevOps, and CI/CD practices.
• Document technical decisions and communicate complex concepts effectively to technical and non-technical stakeholders.

Skills

Python

LLMs

RAG

Prompt engineering

Multi-agent orchestration

LangGraph

LangChain

Cloud AI services

Data pipelines

ETL

Metadata catalogs

Ontologies

Secure coding

CI/CD

REST APIs

SDK integrations

Tools

LangGraph

LangChain

AWS GovCloud

Google GovCloud

Azure IL5+

Vertex AI

AWS Bedrock

OpenAI Enterprise

Anthropic for Gov

Gemini Enterprise

Grok Enterprise

Job description

YO AI Labs seeks an experienced AI/ML Engineer to design, build, and deploy secure, scalable AI systems. You will work with LLMs, RAG, prompt engineering, and multi-agent architectures to create production-grade ML applications. Strong cloud deployment experience and a focus on secure coding are required.

The role emphasizes collaboration with product and security teams, REST API and SDK integration, and ongoing documentation of technical decisions. Remote work is supported.