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Remote Aws Security Jobs in California (NOW HIRING)

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

AI/ML Engineer - Remote

Palo Alto, CA · Remote

$200 - $350/hr

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

AI/ML Engineer - Remote

San Jose, CA · Remote

$200 - $350/hr

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure ... Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.

Showing results 21-40

Remote Aws Security information

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Infographic showing various Remote Aws Security job openings in California as of August 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

AI/ML Engineer - Remote

YO AI Labs

San Francisco, CA • Remote

$200 - $350/hr

Full-time

Posted 6 days ago


Job description

AI/ML Engineer

Job Type: Full-Time
Location: Remote

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.

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.