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Assistant Retrieval Augmented Generation Jobs (NOW HIRING)

AI Voice Engineer

Los Angeles, CA · On-site

$140 - $220/hr

Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows. * Collaborate with product managers, AI engineers, and software developers to ...

New

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

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Assistant Retrieval Augmented Generation information

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How much do assistant retrieval augmented generation jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for assistant retrieval augmented generation in the United States is $23.17, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $25.96 per hour, depending on experience, location, and employer.

What is the difference between Assistant Retrieval Augmented Generation vs Data Analyst?

AspectAssistant Retrieval Augmented GenerationData Analyst
Required CredentialsKnowledge of AI, NLP, and retrieval systemsBachelor's in Statistics, Data Science, or related fields
Work EnvironmentTech companies, AI development teamsBusiness, finance, healthcare sectors
Industry UsageAI, machine learning, natural language processingData analysis, reporting, decision support

Assistant Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, often requiring expertise in AI and NLP. Data Analysts interpret data to generate insights, primarily using statistical tools. While both roles involve working with data, Assistant Retrieval Augmented Generation is centered on AI model development, whereas Data Analysts focus on data interpretation and reporting.

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Infographic showing various Assistant Retrieval Augmented Generation job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 75% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $48,191 per year, or $23.2 per hour.

AI Voice Engineer

Westlake Services, LLC

Los Angeles, CA • On-site

$140 - $220/hr

Other

Posted yesterday

New


Job description

This role involves working with state-of-the-art speech recognition, speech synthesis, voice streaming, and AI agent frameworks to create scalable voice solutions for customer service, sales, finance, and automation applications. This is an on-site position with no relocation assistance provided.

If you're passionate about conversational AI and enjoy solving challenging engineering problems, we'd love to hear from you.

Responsibilities
  • Design and develop real-time voice-to-voice AI agents.
  • Build conversational AI systems using LLMs and agent frameworks.
  • Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies into production applications.
  • Optimize latency and streaming performance for natural conversations.
  • Develop backend services and APIs using Python and C#/.NET.
  • Integrate with telephony, voice streaming, and communication platforms.
  • Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows.
  • Collaborate with product managers, AI engineers, and software developers to deliver production-ready AI solutions.
  • Evaluate emerging AI models, speech technologies, and voice platforms.
  • Monitor, troubleshoot, and continuously improve voice agent performance and reliability.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
  • 5+ years of professional software engineering experience.
  • Hands-on experience building voice-to-voice AI applications.
  • Strong understanding of:
    • Speech Recognition (Automatic Speech Recognition - ASR)
    • Speech Synthesis (Text-to-Speech - TTS)
    • Voice Activity Detection (VAD)
    • Audio streaming and low-latency communication
  • Professional experience with Python and C#/.NET.
  • Experience consuming AI APIs and working with LLMs.
  • Experience building REST APIs and microservices.
  • Knowledge of asynchronous programming, event-driven architectures, and real-time streaming.
  • Strong debugging, analytical, and problem-solving skills.
Preferred Qualifications

Experience with one or more of the following:

  • Real-time conversational AI platforms
  • AI agent frameworks
  • Retrieval-Augmented Generation (RAG)
  • Prompt engineering and evaluation
  • WebRTC, SIP, RTP, or telephony integrations
  • Azure AI, Azure OpenAI, or other cloud AI services
  • Docker and Kubernetes
  • CI/CD pipelines and cloud-native application development
Responsibilities
  • Design and develop real-time voice-to-voice AI agents.
  • Build conversational AI systems using LLMs and agent frameworks.
  • Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies into production applications.
  • Optimize latency and streaming performance for natural conversations.
  • Develop backend services and APIs using Python and C#/.NET.
  • Integrate with telephony, voice streaming, and communication platforms.
  • Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows.
  • Collaborate with product managers, AI engineers, and software developers to deliver production-ready AI solutions.
  • Evaluate emerging AI models, speech technologies, and voice platforms.
  • Monitor, troubleshoot, and continuously improve voice agent performance and reliability.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
  • 5+ years of professional software engineering experience.
  • Hands-on experience building voice-to-voice AI applications.
  • Strong understanding of:
    • Speech Recognition (Automatic Speech Recognition - ASR)
    • Speech Synthesis (Text-to-Speech - TTS)
    • Voice Activity Detection (VAD)
    • Audio streaming and low-latency communication
  • Professional experience with Python and C#/.NET.
  • Experience consuming AI APIs and working with LLMs.
  • Experience building REST APIs and microservices.
  • Knowledge of asynchronous programming, event-driven architectures, and real-time streaming.
  • Strong debugging, analytical, and problem-solving skills.
Preferred Qualifications

Experience with one or more of the following:

  • Real-time conversational AI platforms
  • AI agent frameworks
  • Retrieval-Augmented Generation (RAG)
  • Vector databases
  • Prompt engineering and evaluation
  • WebRTC, SIP, RTP, or telephony integrations
  • Azure AI, Azure OpenAI, or other cloud AI services
  • Docker and Kubernetes
  • CI/CD pipelines and cloud-native application development

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.

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