Mental Health Expert - Remote

YO AI Labs

Austin (TX)

Remote

USD 120,000 - 170,000

Full time

8 hours ago
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Job summary

YO AI Labs is seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives. You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications.

Responsibilities include designing and implementing AI/ML solutions, deploying across secure cloud environments, building data pipelines and APIs, collaborating with product and security teams, and following

Qualifications

  • Proven experience building production AI/ML systems with Python.
  • Experience with LLMs, RAG, and prompt engineering in production.
  • Cloud AI services across GovClouds and enterprise platforms.
  • Experience designing data pipelines, ETL, metadata catalogs, ontologies.
  • Security-conscious coding and CI/CD practices.
  • Excellent written and verbal communication.

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
Cloud AI services
Secure coding
CI/CD
REST APIs
SDK integrations
Communication

Tools

LangGraph
LangChain
AWS GovCloud
Google GovCloud
Azure IL5+
Vertex AI
AWS Bedrock

Job description

Job Summary

We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure. You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications.

Job Type

Full-Time

Location

Remote

Key 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.
Required Skills & Qualifications
  • Strong Python proficiency for AI/ML development, including REST APIs and SDK integrations.
  • Hands-on production experience with LLMs, RAG, and prompt engineering.
  • Experience with multi-agent orchestration, tool use, LangGraph, and LangChain.
  • Strong knowledge of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
  • Experience building data pipelines, ETL processes, metadata catalogs, and ontologies.
  • Strong understanding of secure coding and CI/CD practices.
  • Excellent written and verbal communication skills.
Preferred Qualifications
  • Experience with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
  • Knowledge of MCP, metadata catalog platforms, and advanced API development.
  • Experience working in government, regulated, or security-sensitive cloud environments.
  • Familiarity with relevant compliance and security standards.
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