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Rag Jobs in Oregon (NOW HIRING)

Tebra

Senior AI Automation Engineer

OR · Remote

$103K - $136K/yr

Data/RAG Pipeline Design & Management * * Design and automate data flow processes to support AI retrieval (RAG) and insights generation across core enterprise platforms. * Build evaluation into every ...

LTS

Lead AI Architect/Strategist

OR · Remote

Design and evaluate RAG architectures, including data ingestion, embeddings, vector search, retrieval strategies, and model orchestration. * Lead technical evaluations of emerging AI technologies ...

New

LTS

OR

Design, build, and maintain enterprise AI platform capabilities supporting Large Language Models (LLMs), AI agents, RAG, and Generative AI applications. * Develop reusable AI harnesses to automate ...

New

iHerb

OR

$122K - $161K/yr

RAG and personalization, agent framework and tool use, evals and guardrails, and LLM application development for internal business functions such as marketing automation and BI agents. Job ...

Vectara

Machine Learning (ML) Engineer

OR · On-site +1

Our enterprise RAG Platform offers unparalleled Accuracy, Security, and Explainability by leveraging the strongest models for retrieval, embedding, reranking , a optimized LLM trained for quality ...

Vectara

OR · On-site

$122K - $161K/yr

Our enterprise RAG Platform offers unparalleled Accuracy, Security, and Explainability by leveraging the strongest models for retrieval, embedding, reranking , an optimized LLM trained for quality ...

Gruve

AI Vibe Coding Engineer

OR · Remote

$64K - $72K/yr

Strong understanding of LLMs, RAG architectures, prompt engineering, AI agents, and MCP Preferred Qualification * Experience building GenAI applications * Familiarity with vector databases and ...

Corvel

Data Scientist II

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

Robots and Pencils

OR

$64.75 - $85/hr

Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch.

Robots and Pencils

OR

$64.75 - $85/hr

Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch.

Beyondsoft Consulting

AI Integration: Assist in implementing and testing agentic workflows and advanced RAG (Retrieval-Augmented Generation) patterns, including Graph RAG and Agentic RAG. * Backend Development: Contribute ...

RTI International

Help develop retrieval-augmented generation (RAG) pipelines and agent-based workflows. * Build and consume REST APIs and cloud-native services. * Write clean, maintainable, well-tested code using AI ...

Yubico Inc.

OR

Generative Search & RAG Savvy: A strategic understanding of how Large Language Models (LLMs), vector databases, and Retrieval-Augmented Generation (RAG) systems crawl, parse, and recommend technical ...

iHerb

OR · On-site

This spans the user-facing AI layer (Wellness Agent, LLM-driven recommendations, RAG over catalog and reviews, generative content) and the shared AI infrastructure (RAG pipelines, evals framework ...

EM Key Solutions Inc

AI Engineer

OR · On-site +1

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

EM Key Solutions Inc

Temporary AI Engineer

OR · On-site +1

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

Smarsh

OR

$122K - $161K/yr

Design and optimize retrieval-augmented generation (RAG) pipelines, including handling long documents and retrieval quality * Contribute to knowledge graph-driven approaches to enhance search ...

Autodesk

Senior Software Engineer, Agentic AI

Portland, OR · On-site

$129K - $171K/yr

Experience with RAG, proactive or event-driven agents, and applying agentic AI to engineering workflows, operational automation, or DevOps * Experience designing LLM evaluation frameworks, multi ...

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All JobsRag JobsRag Jobs in Oregon

Rag information

See Oregon salary details

$42.8K

$83.3K

$125.3K

How much do rag jobs pay per year?

As of Aug 1, 2026, the average yearly pay for rag in Oregon is $83,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,500.00 and $98,900.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in programming, data analysis, and experience with AI frameworks, and may involve leadership responsibilities or specialized expertise in areas like deep learning or natural language processing.

Is RAG in demand?

RAG (Retrieval-Augmented Generation) is an emerging technology in the AI and machine learning fields, increasingly used in applications like chatbots and data analysis. Demand for skills in RAG and related AI tools is growing as organizations seek advanced natural language processing solutions. Professionals with knowledge of AI models, data retrieval, and programming languages such as Python are increasingly sought after in this area.

What are RAGs in the context of AI and machine learning jobs?

RAG stands for Retrieval-Augmented Generation, a model architecture that combines information retrieval with generative AI. In this role, a RAG specialist or engineer works on designing, implementing, and optimizing systems that retrieve relevant data from large databases to provide more accurate and informed AI-generated responses. This position typically requires strong knowledge of natural language processing, information retrieval, and deep learning frameworks. RAG models are particularly useful in applications like customer support, search engines, and knowledge management systems.

What are the key skills and qualifications needed to thrive as a RAG Engineer, and why are they important?

To thrive as a Retrieval-Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and software engineering, often with a degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience with vector databases, and knowledge of APIs for language models are typically required. Problem-solving, effective communication, and adaptability are crucial soft skills for collaborating with teams and navigating evolving technologies. These skills are important to successfully develop, deploy, and maintain RAG systems that enhance the performance and relevance of AI-driven applications.

What is a RAG job?

A RAG job typically refers to a role involving Red, Amber, and Green (RAG) status reporting, often used in project management to indicate progress or risk levels. Such jobs may require skills in data analysis, reporting tools, and project coordination to monitor and communicate project health effectively.

What is the difference between Rag vs Data Analyst?

AspectRagData Analyst
Required CredentialsVaries, often no formal degreeBachelor's degree in data-related field, often certifications
Work EnvironmentFieldwork, on-site, or warehouse settingsOffice-based, computer-focused
Employer & Industry UsageConstruction, manufacturing, logisticsFinance, marketing, healthcare, tech
Common Search & ComparisonRag vs Data AnalystData Analyst roles and responsibilities

While Rags typically work in physical environments handling materials or equipment, Data Analysts focus on interpreting data to inform business decisions. Both roles require analytical skills but differ significantly in credentials, work setting, and industry applications.

What are some common challenges faced by RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

RAG engineers often encounter challenges in ensuring the seamless integration of retrieval systems with large language models, such as maintaining low latency while fetching relevant documents and ensuring retrieved data is contextually appropriate for generation tasks. Balancing retrieval accuracy and computational efficiency is key, especially when dealing with large-scale or real-time applications. Effective collaboration with data engineers, NLP researchers, and product teams is essential to continuously refine retrieval pipelines and improve the relevance of generated outputs.

What jobs pay 500,000 a year in the US?

High-paying jobs that can reach or exceed $500,000 annually in the US include roles such as senior corporate executives, investment bankers, specialized surgeons, and successful entrepreneurs. These positions often require advanced degrees, extensive experience, and strong industry networks, with compensation frequently including bonuses, stock options, or profit sharing.
What are the most commonly searched types of Rag jobs in Oregon? The most popular types of Rag jobs in Oregon are:
What are popular job titles related to Rag jobs in Oregon? For Rag jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Rag jobs in Oregon look for? The top searched job categories for Rag jobs in Oregon are:
Rag jobs near you
Infographic showing various Rag job openings in Oregon as of July 2026, with employment types broken down into 75% Full Time, 9% Part Time, 2% Temporary, and 14% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $83,265 per year, or $40 per hour.

Senior AI Automation Engineer

Tebra

OR • Remote

$103K - $136K/yr

Other

Re-posted 29 days ago

Job description

About the Role

We are seeking a hands-on AI & Automation Engineer to design, build, and optimize integrations, automations, and advanced AI workflows, including agentic architecture, that power our enterprise business operations. You'll own the Workato automation stack, engineer scalable AI workflows on top of core platforms (Salesforce, NetSuite, Snowflake, Slack), and implement agentic capabilities that allow systems to act as intelligent tools, reducing manual work and accelerating insights.

This role requires deep technical execution skills in integration development, agentic system design, and programming, combined with a practical understanding of AI workflows. You will collaborate directly with stakeholders to translate business needs into scalable, automated solutions and deliver measurable improvements in system efficiency and operational performance.

Your Area of Focus

Integration & Automation Development

    • Design, build, and maintain Workato recipes, connectors, and orchestrations for Salesforce, NetSuite, Slack, and Snowflake.
    • Implement error handling, observability, and reusable design patterns to ensure reliability and scalability.

Agentic System Design

    • Architect multi-agent systems: tool selection, planning loops, state management, human-in-the-loop Checkpoints.
    • Partner with stakeholders to design corporate systems (Salesforce, NetSuite, Snowflake, Slack, etc) as agent-callable tools, not just data sources.
    • Build guardrails, fallbacks and error recovery for non-deterministic workflows.

Data/RAG Pipeline Design & Management

    • Design and automate data flow processes to support AI retrieval (RAG) and insights generation across core enterprise platforms.
    • Build evaluation into every system to ensure high quality results, considering precision, answer faithfulness, latency, and cost.
    • Own the Retrieval-Augmented Generation (RAG) lifecycle end-to-end, including ingestion, chunking strategy, embeddings, vector storage, and reranking.
    • Implement data quality checks and architectural safeguards to ensure trusted, high-fidelity datasets for AI agents.

AI Operations

    • Production observability: prompt/response tracing, cost monitoring, eval dashboards.
    • Document agent behavior, decision logic and failure modes.
    • A/B testing agent versions, model comparisons.

Programming for Automation

    • Write modular, reusable scripts in Python, Ruby, SQL, or JavaScript to support integration, data transformation, and automation tasks.

Governance & Documentation

    • Apply data governance practices for lineage, security, and retention.
    • Maintain technical documentation, diagrams, and version control via GitHub, Confluence, and Jira.
Your Professional Qualifications
  • 5+ years of experience in integration, automation, AI, or software engineering, with 1+ year hands-on in Workato.
  • Proven expertise with Enterprise iPaaS required (Workato, Mulesoft, or similar).
  • Deep proficiency in designing, implementing, and architecting complex AI workflows and integrations across core platforms (Salesforce, NetSuite, Slack, and Snowflake).
  • Hands-on technical background in programming (Python, Ruby, or similar), leveraging APIs to build and maintain scalable, high-fidelity enterprise systems.
  • Experience using vector databases such as Pinecone, Snowflake Cortex Search, and pgvector for Retrieval-Augmented Generation (RAG).
  • Experience with AI/ML concepts and implementing agentic architecture and AI workflows in enterprise environments.
  • Experience with Cloud Platforms such as GCP or AWS preferred.
  • Experience with GitHub for version control, Jira for work tracking, and Confluence/Lucid for documentation.
  • Strong problem-solving, critical thinking, and ability to execute under minimal supervision.
  • Motivated to learn new technologies and develop new skills.
  • Track record of introducing innovation in automation and AI while maintaining governance and system reliability.
  • Workato Automation Pro , Foundations or SnowPro certifications preferred.

(For Recruiter use only) #LI-SS1 #LI-Remote

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