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Freelance Retrieval Augmented Generation Jobs in Missouri

Retrieval-Augmented Generation (RAG) * Application Logic * Hybrid AI Patterns * Mentor engineers, conduct code reviews, and establish engineering best practices. * Parallelize delivery across ...

Senior AI Engineer (Java)

Saint Louis, MO · On-site

$121K - $159K/yr

Design and deploy LLM workflows involving prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG). Develop integrations between Java applications and Python-based AI/ML or model ...

Senior AI Engineer (Java)

Saint Louis, MO · On-site

$117K - $154K/yr

Design and deploy LLM workflows involving prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG). * Develop integrations between Java applications and Python-based AI/ML or model ...

AI Agentic Tester Denver, MO (Remote) Must-Have Skills AI Agentic Testing Functional Testing Generative AI Testing Large Language Models (LLMs) AI Agents & Agentic AI Retrieval-Augmented Generation ...

Retrieval-Augmented Generation (RAG) * Prompt Engineering Validation * AI Model Validation & Evaluation * API Testing (Postman, REST APIs, Swagger) * Python * Test Automation (Selenium / Playwright ...

Senior AI Platform Engineer

Saint Louis, MO · On-site

$99K - $136K/yr

You will help evolve our platform from Retrieval-Augmented Generation (RAG) applications to agentic AI systems that leverage reasoning, orchestration, tool use, and autonomous workflows. You will ...

Optimize retrieval-augmented generation (RAG) solutions through embedding evaluation, metadata design, reranking approaches, citation quality assessment, and knowledge freshness validation. * Develop ...

$80K - $110K/yr

Design retrieval-augmented generation solutions and integrate vector databases to support accurate and context-aware AI applications. * Develop sophisticated prompt-engineering strategies to improve ...

Optimize retrieval-augmented generation (RAG) solutions through embedding evaluation, metadata design, reranking approaches, citation quality assessment, and knowledge freshness validation. Develop ...

Develop solutions incorporating large language models, retrieval-augmented generation, workflow automation, copilots, and agentic AI orchestration where appropriate. * Define solution architectures ...

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

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Freelance Retrieval Augmented Generation information

What is a freelance retrieval augmented generation specialist?

A Freelance Retrieval Augmented Generation (RAG) specialist is an independent professional who designs, develops, and implements AI systems that combine retrieval-based methods with generative models. RAG specialists help organizations enhance their applications by integrating large language models (LLMs) with external data sources, allowing the AI to access and utilize up-to-date information beyond its training data. Their work involves tasks such as building pipelines for document indexing and retrieval, fine-tuning models, and optimizing the integration for accuracy and efficiency. Freelance RAG specialists typically work on a contract basis, offering flexibility and expertise for businesses that need advanced AI solutions.

What are the key skills and qualifications needed to thrive as a freelance retrieval augmented generation specialist?

To thrive as a Freelance Retrieval Augmented Generation (RAG) Specialist, you need expertise in natural language processing, information retrieval, and machine learning, typically supported by a degree in computer science or related fields. Proficiency with frameworks like Hugging Face Transformers, vector databases (e.g., FAISS, Pinecone), and cloud platforms is often required. Strong problem-solving, effective communication, and adaptability set standout professionals apart in this role. These skills ensure the development and fine-tuning of high-performance RAG systems that deliver accurate, contextually relevant results for clients.

How does a freelance retrieval augmented generation specialist typically collaborate with client teams during a project?

Freelance Retrieval Augmented Generation (RAG) specialists often work closely with client data scientists, engineers, and project managers to understand business requirements and integrate RAG systems into existing workflows. Communication is usually handled through regular virtual meetings, shared documentation, and sometimes real-time collaboration tools. Freelancers are expected to deliver modular, well-documented solutions and provide guidance on optimizing retrieval pipelines or fine-tuning models. This collaborative dynamic ensures that RAG implementations are aligned with client goals and technical standards, while also allowing freelancers to contribute innovative solutions based on their expertise.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Missouri?

The most popular types of Retrieval Augmented Generation jobs in Missouri are:

What are popular job titles related to Freelance Retrieval Augmented Generation jobs in Missouri?

For Freelance Retrieval Augmented Generation jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Freelance Retrieval Augmented Generation jobs in Missouri look for?

The top searched job categories for Freelance Retrieval Augmented Generation jobs in Missouri are:

Principal Agentic AI Engineer

Exavalu

California, MO • On-site

$140 - $200/hr

Other

Posted 25 days ago


Job description

Exavalu Solutions India Pvt Ltd | Full time

Exavalu is a US based consulting firm specialized in Digital Transformation Advisory and Digital Solution Delivery for select industries like Insurance, Healthcare and Financial Services. Our Headquarters is in California, US with multiple offices across US, Canada, and delivery centres in India. We were founded by Industry executives and Consulting principals with deep industry experience that allows us to bring advisory strength and solution expertise to clients. We’re in a hyper growth trajectory growing at over 100% year on year.

Join our diverse and inclusive team where you will feel valued and motivated to contribute with your unique skills and experience.

Exavalu offers permanent remote working model as we believe in going where the right talent is.

Job Description

This is a remote position.

Overview

We are seeking an experienced Agentic AI Technical Lead to lead a high-impact Agentic AI SWAT Pod responsible for delivering next-generation AI solutions across strategic business use cases.

This is a hands-on technical leadership role where you will architect, build, review, troubleshoot, and deploy production-grade AI applications while mentoring a compact engineering team. You will drive the adoption of modern Agentic AI architectures, intelligent workflows, Retrieval-Augmented Generation (RAG), and orchestration frameworks to deliver scalable enterprise AI solutions.

The ideal candidate should possess a strong software engineering background with recent hands-on coding experience in AI applications and have successfully delivered production-grade LLM, RAG, or Agentic AI solutions.

Key Responsibilities
Technical Leadership
  • Lead a compact Agentic AI SWAT Pod across multiple AI use-case tracks.
  • Drive technical architecture and implementation for enterprise Agentic AI solutions.
  • Select the most appropriate solution architecture using:
    • Agentic AI
    • Workflow Automation
    • Retrieval-Augmented Generation (RAG)
    • Application Logic
    • Hybrid AI Patterns
  • Mentor engineers, conduct code reviews, and establish engineering best practices.
  • Parallelize delivery across multiple workstreams while ensuring technical consistency.
AI Solution Development
  • Design and develop production-ready AI agents and autonomous workflows.
  • Build intelligent AI systems using:
    • Large Language Models (LLMs)
    • Agentic AI
    • RAG architectures
    • Multi-agent orchestration
  • Develop reusable AI components and reference implementations.
  • Own critical code paths and contribute to hands-on software development.
Agent Orchestration & Integration

Take ownership of:

  • Agent orchestration
  • Context management
  • AI workflow readiness
  • AI service integrations
  • Design scalable, secure, and maintainable AI platforms.
  • Troubleshoot production issues and optimize AI workloads.
  • Implement CI/CD best practices for AI applications.
  • Build observability into AI systems using modern monitoring frameworks.
  • Ensure engineering quality through testing, code reviews, and deployment automation.
Required Skills & Experience
  • 10+ years of software engineering, platform engineering, or AI development experience.
  • Recent hands-on coding experience in production environments.
  • Large Language Model (LLM) applications
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI solutions
  • Strong software engineering fundamentals.
  • Experience building scalable enterprise AI applications.
  • Strong understanding of API development, cloud-native architecture, and distributed systems.
  • Experience implementing CI/CD pipelines and production monitoring.
Primary Skills
Programming Languages
  • Python
  • Java
  • TypeScript
  • Agentic AI
  • Retrieval-Augmented Generation (RAG)
  • AI Assistants
  • AI Orchestration
  • Prompt Engineering
Frameworks & Technologies
  • LangGraph
  • AI Workflow Orchestration
  • REST APIs
DevOps
  • Git
  • Deployment Automation
Observability
  • OpenTelemetry
  • Performance Optimization
Secondary Skills (Good to Have)
  • LangChain
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • Knowledge Graphs
  • Multi-Agent Systems
  • Docker
  • Distributed Systems
  • MLOps
  • AI Governance
RequirementsRequired Skills & Experience
  • 10+ years of software engineering, platform engineering, or AI development experience.
  • Recent hands-on coding experience in production environments.
  • Large Language Model (LLM) applications
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI solutions
  • Strong software engineering fundamentals.
  • Experience building scalable enterprise AI applications.
  • Strong understanding of API development, cloud-native architecture, and distributed systems.
  • Experience implementing CI/CD pipelines and production monitoring.
Primary Skills
Programming Languages
  • Python
  • Java
  • TypeScript
  • Agentic AI
  • Retrieval-Augmented Generation (RAG)
  • AI Assistants
  • AI Orchestration
  • Prompt Engineering
Frameworks & Technologies
  • LangGraph
  • AI Workflow Orchestration
  • REST APIs
DevOps
  • Git
  • Deployment Automation
Observability
  • OpenTelemetry
  • Performance Optimization
Secondary Skills (Good to Have)
  • LangChain
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • Knowledge Graphs
  • Multi-Agent Systems
  • Docker
  • Distributed Systems
  • MLOps
  • AI Governance

Diversity Inclusion:

At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career.

Exavalu also promotes flexibility depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also have a welcome back program to help people get back to the mainstream after a long break due to health or family reasons.

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