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Salaried Rag Jobs in Missouri (NOW HIRING)

Jobgether

$100K - $120K/yr

... salary of $100,000-$120,000 . * Full-time opportunity with a remote working model . * Opportunity to work on cutting-edge AI, machine learning, and GenAI solutions. * Hands-on exposure to LLMs, RAG ...

Quovy

Forward Deployed Engineer

California, MO · On-site

$120 - $180/hr

Competitive salary + equity and benefits Quovy builds an AI operating layer for specialty insurance ... Nice to have * 01 Experience integrating LLMs, RAG, or other AI models into production systems ...

New

Perficient

FDE with Amazon Connect

Saint Louis, MO · On-site

$73K - $170K/yr

Retrieval-augmented generation (RAG) for knowledge base queries * Guardrails configuration, model ... The new hire salary range displays the minimum and maximum salary targets for this position across ...

Perficient, Inc.

FDE with Amazon Connect

Saint Louis, MO

$73K - $145K/yr

Retrieval-augmented generation (RAG) for knowledge base queries * Guardrails configuration, model ... The new hire salary range displays the minimum and maximum salary targets for this position across ...

Perficient, Inc.

Forward Deployed Engineer

Saint Louis, MO · Remote

$118K - $202K/yr

... LLMs, RAG, agents) * Proficient in leveraging AI technologies to drive innovation, support ... The new hire salary range displays the minimum and maximum salary targets for this position across ...

KlearNow.ai

Senior AI Engineer

California, MO · On-site

$187 - $215/hr

Agent architectures, LLM systems, and RAG pipelines * Retrieval, grounding, and orchestration ... The US salary range for this position is $187k to $215k in the San Jose Bay Area, California $187 ...

US Bank

Data Scientist

Earth City, MO · On-site

$111K - $131K/yr

Knowledge of Retrieval-Augmented Generation (RAG) frameworks. * Experience with Azure AI, Azure ... Paid vacation (from two to five weeks depending on salary grade and tenure) * Up to 11 paid holiday ...

Kforce Technology Staffing

SRE (AI/ML)

Maryland Heights, MO · On-site

$55 - $73.25/hr

... LLM/RAG solutions. The role blends classic SRE and cloud administration with modern MLOps and ... Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off ...

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All JobsSalaried Rag JobsSalaried Rag Jobs in Missouri

Salaried Rag information

What is the difference between Salaried Rag vs Salaried Technician?

AspectSalaried RagSalaried Technician
Required CredentialsHigh school diploma or equivalent, specialized trainingHigh school diploma, technical certification or associate degree
Work EnvironmentOffice or field-based, depending on industryIndustrial, manufacturing, or technical settings
Employer & Industry UsageMedia, printing, or creative industriesManufacturing, maintenance, or technical services
Common Search & ComparisonYesYes

The comparison shows that Salaried Rag and Salaried Technician share similar credential requirements and are used in related industries. Salaried Rag typically refers to roles in media or creative fields, while Salaried Technician is common in technical and industrial sectors. Both roles involve specialized skills and are salaried positions, but their work environments and industry applications differ.

What are the most commonly searched types of Rag jobs in Missouri?

The most popular types of Rag jobs in Missouri are:

What are popular job titles related to Salaried Rag jobs in Missouri?

For Salaried Rag jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Salaried Rag jobs in Missouri look for?

The top searched job categories for Salaried Rag jobs in Missouri are:

What cities in Missouri are hiring for Salaried Rag jobs?

Cities in Missouri with the most Salaried Rag job openings:

Salaried Rag jobs near you

AI/ML & Forward Deployed Engineer

Jobgether

On-site, Remote

$100K - $120K/yr

Full-time

Posted 11 days ago

Key responsibilities

  • Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.

  • Build scalable AI services and integrations using APIs and event-driven architectures, and support solutions through production operations.

  • Establish and maintain MLOps and LLMOps practices covering deployment, automation, monitoring, and lifecycle management.

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML & Forward Deployed Engineer based in Netherlands.

This role offers the opportunity to build and deploy high-impact AI, machine learning, and generative AI solutions from initial concept through production.
You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create scalable and reliable AI products.
The position involves solving complex business problems through technologies such as LLMs, RAG pipelines, NLP, forecasting, and anomaly detection.
You will work across the full AI lifecycle, from experimentation and evaluation to deployment, monitoring, and continuous improvement.
Strong attention to security, governance, observability, and data quality will be essential when delivering production-ready solutions.
You will also collaborate closely with stakeholders to translate business needs into practical technical solutions and measurable outcomes.
This is an excellent opportunity for an experienced engineer who enjoys combining advanced AI technologies with hands-on implementation and real-world impact.

Accountabilities
  • Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.
  • Build and optimize ML models and applications covering deep learning, NLP, forecasting, classification, regression, and anomaly detection use cases.
  • Develop production-grade GenAI applications using LLMs, RAG pipelines, embeddings, retrieval optimization, reranking, and prompt engineering.
  • Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and performance.
  • Build scalable AI services and integrations using REST and gRPC APIs as well as event-driven architectures.
  • Establish and maintain MLOps and LLMOps practices covering deployment, automation, versioning, monitoring, and lifecycle management.
  • Containerize and orchestrate AI applications using Docker and Kubernetes and integrate them into robust CI/CD pipelines.
  • Implement model monitoring, drift detection, performance tracking, and processes for continuous model improvement.
  • Ensure AI solutions meet enterprise requirements for data quality, governance, security, role-based access control, encryption, and auditability.
  • Collaborate with business and technical stakeholders to understand requirements, identify opportunities for AI adoption, and translate them into effective technical solutions.
  • Support solutions through production operations, troubleshooting, optimization, and ongoing improvements.
  • Apply strong engineering practices to ensure AI systems are scalable, secure, observable, maintainable, and aligned with business objectives.
Requirements
  • 8+ years of professional software engineering or technical engineering experience.
  • Strong hands-on experience in Machine Learning and AI/ML Engineering.
  • Advanced Python development skills and practical experience with deep learning and machine learning techniques.
  • Experience with NLP, forecasting, classification, regression, and anomaly detection.
  • Proven experience building GenAI applications using LLMs and Retrieval-Augmented Generation (RAG) architectures.
  • Strong understanding of embeddings, retrieval tuning, reranking, prompt engineering, and AI/LLM evaluation methodologies.
  • Solid knowledge of MLOps and LLMOps principles and practices across the AI development lifecycle.
  • Hands-on experience with Docker, Kubernetes, and CI/CD technologies for production deployments.
  • Experience designing and developing REST and gRPC APIs and event-driven services.
  • Knowledge of model monitoring, model versioning, drift detection, performance evaluation, and model lifecycle management.
  • Strong understanding of data quality, data governance, security controls, RBAC, encryption, and audit trails.
  • Ability to work effectively with both technical and non-technical stakeholders and translate business challenges into practical AI solutions.
  • Strong problem-solving, analytical, communication, and collaboration skills.
  • Ability to operate effectively in fast-moving environments while balancing experimentation with production reliability.
Benefits
  • Competitive annual salary of $100,000-$120,000.
  • Full-time opportunity with a remote working model.
  • Opportunity to work on cutting-edge AI, machine learning, and GenAI solutions.
  • Hands-on exposure to LLMs, RAG, MLOps, LLMOps, Kubernetes, and cloud-native engineering practices.
  • Opportunity to contribute to AI solutions from concept and experimentation through production deployment.
  • Work on technically challenging projects with a strong focus on scalability, security, governance, and observability.
  • Collaborative environment with opportunities to engage directly with stakeholders and influence AI solution strategy.
  • Opportunity to expand expertise across modern AI engineering, machine learning, and production software development.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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