1

Rag Engineer Jobs in Missouri (NOW HIRING)

Production LLM and agentic systems - design multi-step agents with tool use, orchestration, memory, and retrieval-augmented generation (RAG), engineered for reliability and low latency at scale

New

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

Build and evolve RAG and agent-based architectures. * Create evaluation frameworks to improve ... Establish engineering best practices and contribute to code reviews. * Research and adopt emerging ...

Lead AI Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

Lead AI Engineer Location: St. Louis. MO (Hybrid) Duration: 12 Month Contract About the Role We are ... You will help evolve our platform from Retrieval-Augmented Generation (RAG) applications to agentic ...

Senior AI Platform Engineer

Saint Louis, MO · On-site

$99K - $136K/yr

Senior AI Platform Engineer Duration: 12 months+ Location: St. Louis, MO- Hybrid-3 days/week on ... You will help evolve our platform from Retrieval-Augmented Generation (RAG) applications to agentic ...

$80K - $110K/yr

The role offers deep hands-on exposure to technologies such as Claude, LangGraph, RAG, vector ... Beyond engineering, you will provide technical leadership and make key architectural decisions ...

$100K - $120K/yr

You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create ... The position involves solving complex business problems through technologies such as LLMs, RAG ...

Senior AI Engineer

O Fallon, MO · Hybrid

$97K - $134K/yr

Title and Summary Senior AI Engineer Mastercard's Business & Market Insights (B&MI) group empowers ... Build production-grade RAG and Graph-RAG systems integrating vector databases (Pinecone, pgvector ...

$80K - $110K/yr

The role combines hands-on work with LLMs, AI agents, RAG, tool calling, and AI workflows with strong data engineering and platform engineering practices. You will leverage modern cloud and data ...

Senior AI Engineer

O Fallon, MO · On-site

$97K - $134K/yr

Title and Summary Senior AI Engineer Mastercard's Business & Market Insights (B&MI) group empowers ... RAG and Graph-RAG systems integrating vector databases (Pinecone, pgvector, OpenSearch) and ...

RAG pipelines, vector search, embedding infrastructure, or retrieval‑augmented applications at ... engineering experience, with a significant portion at senior, staff, or principal IC level.

RAG and personalization, agent framework and tool use, evals and guardrails, and LLM application ... Understanding of prompt engineering, context window management, and LLM output quality tradeoffs.

New

(USA) Software Engineer III

Anderson, MO · On-site

$90K - $180K/yr

The engineer leads small to medium projects, drives continuous improvement, and supports business ... RAG & MCP: Experience developing Retrieval-Augmented Generation (RAG) applications and working with ...

The engineer leads small to medium projects, drives continuous improvement, and supports business ... RAG & MCP: Experience developing Retrieval-Augmented Generation (RAG) applications and working with ...

(USA) Software Engineer III

Noel, MO · On-site

$90K - $180K/yr

The engineer leads small to medium projects, drives continuous improvement, and supports business ... RAG & MCP: Experience developing Retrieval-Augmented Generation (RAG) applications and working with ...

$94K - $124K/yr

The role combines strong software engineering with practical expertise in RAG, embeddings, agents, tool calling, and AI orchestration. You will work closely with Product, ML, and Engineering teams to ...

New

next page

Showing results 1-20

Rag Engineer information

See Missouri salary details

$55.8K

$84.9K

$144K

How much do rag engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for rag engineer in Missouri is $84,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,300.00 and $98,500.00 per year, depending on experience, location, and employer.

What is the difference between Rag Engineer vs Textile Technician?

AspectRag EngineerTextile Technician
Required CredentialsEngineering degree, technical certificationsDiploma or degree in textiles or related field
Work EnvironmentFactories, manufacturing plants, R&D labsTextile mills, production facilities, quality control labs
Industry UsageDesigning and improving rag production processesMonitoring textile quality, testing fabrics

While both roles involve working within the textile industry, a Rag Engineer primarily focuses on the engineering aspects of rag production, process optimization, and machinery, whereas a Textile Technician concentrates on fabric testing, quality control, and ensuring textile standards are met. The roles often overlap in industry settings but differ in technical focus and responsibilities.

How to become a rag engineer?

To become a rag engineer, you typically need a bachelor's degree in engineering, materials science, or a related field. Relevant skills include knowledge of manufacturing processes, quality control, and proficiency with industry tools and equipment; certifications in quality management or safety can also be beneficial. Gaining experience through internships or entry-level positions in manufacturing environments is important for career advancement.

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

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

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

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

What cities in Missouri are hiring for Rag Engineer jobs?

Cities in Missouri with the most Rag Engineer job openings:

Infographic showing various Rag Engineer job openings in Missouri as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $84,900 per year, or $40.8 per hour.

Staff AI Engineer, Payments Intelligence

Yuno

On-site

Full-time

Medical

Posted 2 days ago

New


Job description

Remote Full Time Individual Contributor +8 Years of Experience

Staff AI Engineer, Payments Intelligence Who We Are

Yuno is the AI-native operating system of global commerce, powering the financial infrastructure of enterprise merchants, banks, and wallets. Through a single API, Yuno connects them to pay-ins, payouts, fraud prevention, KYC/KYB, and stablecoins globally, so they can operate everywhere. Agnostic by design and connected to 1,000+ payment methods and 460+ integrations in 190+ countries, Yuno optimizes acceptance rates, reduces costs, and strengthens security through specialized AI agents that learn from every transaction. Global brands including McDonald's, NetEase Games, GoFundMe, and Rappi run their payments on Yuno.

About The Role

Yuno is looking for a Staff AI Engineer to be the senior technical leader for Payments Intelligence - the unit building the AI agents and intelligence products that make payments smarter across the platform. You'll architect and build production AI-agent systems like AIDA and NOVA, shape how Yuno applies LLMs and agentic AI to real payment problems, and raise the technical bar for the engineers around you.


This is a hands-on AI leadership role at the frontier. You'll design agents that hold real conversations with customers, recover revenue, automate operations, and surface intelligence to merchants - all in a production, multi-market, compliance-sensitive environment. Your impact comes as much from setting the technical direction for agentic AI as from the systems you build.

What This Unit Owns
  • Yuno Agents (AIDA & NOVA) - AIDA, the agent that retrieves payment data and answers technical questions for support and operations teams; and NOVA, the agents that recover revenue by turning failed payments into intelligent, multilingual customer conversations across channels

  • AI Ops & Support - AI-driven automation that streamlines internal operations and customer support

  • Client Intelligence - the AI and data products that surface insight and intelligence to Yuno's merchants

How AI Shows Up in This Role
  • You're not adding AI to a product - you're building the AI that is the product: the agents, LLM pipelines, and intelligence systems at the core of Payments Intelligence

  • AI is our default execution layer: you're expected to use AI-assisted tooling fluently in your own work, and to define how the unit designs, evaluates, and ships agentic systems responsibly

Your Contribution Will Be
  • Agent architecture and technical leadership - own the architecture of Yuno's AI agents (AIDA, NOVA) and intelligence systems; set the technical direction for agentic AI and raise the bar for the team

  • Production LLM and agentic systems - design multi-step agents with tool use, orchestration, memory, and retrieval-augmented generation (RAG), engineered for reliability and low latency at scale

  • Conversational and multilingual experiences - build agents that hold real, dynamic customer conversations across channels (phone, WhatsApp) and 70+ languages, adapting to context and intent

  • Evaluation, safety, and guardrails - define how the unit measures agent quality and safety, with rigorous evaluation, observability, and guardrails so agents behave reliably in a compliance-sensitive, multi-market environment

  • Intelligence and data products - architect the client-intelligence systems that turn payment data into actionable insight for merchants

  • AI Ops automation - build the AI-driven automation that streamlines internal operations and support

  • Mentorship and cross-functional collaboration - mentor engineers and partner with Product, Data Science, and Staff Engineers across domains to ship complex, cross-team AI work

What Success Looks Like

Within your first 6-12 months, you've led the architecture of at least one core agent or intelligence capability, shipped agentic systems to production with real evaluation and guardrails behind them, and become the technical voice Yuno trusts on how to build AI agents responsibly at scale.

Skills You Need Minimum Qualifications
  • Extensive software engineering experience, with a track record building and shipping production LLM or AI-agent systems

  • Deep expertise in agentic systems - multi-step agents, tool use, orchestration, memory, and retrieval-augmented generation (RAG)

  • Strong LLM application skills - prompt engineering, evaluation, and guardrails for reliable, safe outputs

  • Strong Python for AI/ML, plus solid backend engineering (Go and/or Kotlin) to productionize systems at scale

  • Model serving and LLM inference, with the cloud infrastructure to run AI workloads in production (AWS or similar)

  • Evaluation and observability for AI - hands-on with tools like LangFuse, LangSmith, Braintrust, or MLflow - plus solid automated testing and CI/CD

  • Proven technical leadership - mentoring engineers, driving technical vision, and delivering complex, cross-team projects

  • English - advanced proficiency, written and spoken

Preferred Qualifications
  • Fine-tuning, RLHF, or model customization

  • Vector databases (Pinecone, Weaviate, or FAISS) and embedding retrieval

  • Building agent workflows with MCP servers or modern agent frameworks

  • Conversational AI and speech (speech-to-text / text-to-speech) and multilingual systems

  • Experience in the payments or fintech industry

Nice to Have
  • Running multi-tenant AI platforms or GPU/resource management at scale

  • Data pipelines and orchestration (Airflow, Prefect) and warehouses like Databricks, Snowflake, or BigQuery

  • Spanish proficiency

Tech Stack
  • Languages - Python (AI/ML), Go and Kotlin (platform services)

  • AI & LLMs - LLM APIs and open models, agent frameworks, MCP, RAG

  • AI evaluation & observability - LangFuse, LangSmith, Braintrust, MLflow

  • Data & retrieval - vector databases, feature stores

  • Messaging - Apache Kafka, SQS

  • Databases - PostgreSQL, Redis

  • Infrastructure - AWS, Kubernetes, Docker, Terraform

  • Observability - Datadog, OpenTelemetry

  • CI/CD - GitHub Actions, ArgoCD

  • Version Control - Git / GitHub

What We Offer at Yuno
  • Competitive Compensation

  • Remote Work - you can work from everywhere

  • Home Office Bonus - a one-time allowance to set up your ideal home office

  • Work Equipment

  • Stock Options

  • Health Plan wherever you are

  • Flexible Days Off

  • Language, Professional, and Personal Growth courses

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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 or wish to exercise your data protection rights, please contact us at [email protected].
apply for this job