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Rag Jobs in Oregon (NOW HIRING)

Instacart

Forward Deployed Engineer

OR · On-site +1

Hands-on experience building with LLM APIs, function calling, tool use, agent frameworks, or RAG pipelines-you have shipped something agentic that real users depended on. * Proficiency in Python or ...

BrightView

Enhancements Crew Leader (52/LC)

Tualatin, OR · On-site

$18.75 - $23.75/hr

Ability to work in environments where exposure to allergens such as pollen and rag weed, insects such as bees and spiders and reptiles such as lizards and snakes. BrightView Landscapes, LLC is an ...

NICE

Product Pre-Sales Engineer, AI

OR · On-site +1

Hands-on ability to configure and demo AI agent flows including intent design, LLM tuning, RAG-based knowledge retrieval, and agent orchestration in Cognigy or a comparable conversational AI platform

Natera

Senior Software Engineer (Data & AI Solutions)

OR · On-site +1

$122K - $161K/yr

Exposure to vector databases, embeddings, semantic search, or RAG-based architectures is a plus * Proven ability to operate effectively in fast-paced environments, balancing speed, rigor, and ...

Tebra

Staff Software Engineer, AI Engineering

OR · On-site +1

Practical experience with orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, CrewAI) and a deep understanding of RAG, tool calling, prompt engineering, context/state management, and ...

LTS

Senior Agentic AI Software Engineer

OR · On-site +1

$122K - $161K/yr

Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt ...

BOLD

Senior Prompt Designer II

OR · On-site +1

$101K - $108K/yr

RAG, multi-agent architectures, chain-of-thought, context window management, and model behaviour trade-offs. * Hands-on experience across LLM providers (OpenAI, Anthropic, Google) with clear ...

Attain Talent

Lead AI/ML Engineer

OR · On-site +1

$180K - $230K/yr

Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), or AI agents. * Experience deploying AI solutions using MLOps best practices. * Experience with ...

Five9

Vice President, Engineering and AI Innovations

OR · On-site +1

$179K - $231K/yr

LLMs, RAG systems, embeddings, vector databases, multimodal models. * Practical experience integrating LLMs into production systems, including prompt orchestration, function calling, structured ...

Slalom Consulting

General Information

Portland, OR · On-site

$91K - $115K/yr

... RAG), Cache-Augmented Generation (CAG), prompt engineering, model routing, and how these choices impact cost, performance, scalability, and business value. * Ability to analyze usage, cost, and ...

LTS

Agentic AI Security Engineer

OR · On-site +1

Secure Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector databases, and enterprise knowledge repositories. * Design controls that prevent unauthorized knowledge access, data leakage ...

PointClickCare

(Canada) AI Solutions Specialist

OR · On-site +1

Prompt Engineering & AI Solution Optimization: -Develop, test, and iterate on prompt engineering strategies to maximize model accuracy, consistency, and performance. -Apply RAG (Retrieval-Augmented ...

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Showing results 41-60

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 22, 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 RAG?

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 skills and qualifications are needed to thrive as a RAG engineer?

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 are common challenges faced by RAG 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 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 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 August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $83,265 per year, or $40 per hour.

Forward Deployed Engineer

Instacart

OR • On-site, Remote

Full-time

Re-posted 14 days ago

Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

28th of 64 rated delivery companies

Job description

Overview

Instacart's Enterprise Solutions team is building a first-of-its-kind business: embedding directly with enterprise retail and CPG partners to design, sell, and deliver AI-powered solutions at scale. We are a small, senior, field-first pod - part startup, part consultancy - defining the playbook as we go.

As a Forward Deployed Engineer, you are Instacart's hands-on technical presence inside enterprise customer environments. You will sit inside retailers' and partners' ecosystems, understand their infrastructure, and build agentic AI solutions on top of it. As part of your mission, you will brainstorm with partner technical leaders and collaborate on solution designs that deliver value while remaining compatible with existing environments and infrastructure. You will also collaborate closely with Instacart R&D's team, informing platform evolution and serving as the bridge between what gets built internally and what actually works in the real world.

About the Job
  • Embed with enterprise retail customers and partners to understand their technical environments, data systems, and business workflows.
  • Design, build, and deploy AI and agentic solutions tailored to each customer's specific infrastructure and needs, across Instacart's full platform suite.
  • Extend, adapt, and integrate Instacart's core AI capabilities to fit customer ecosystems,  even when those systems are undocumented or non-standard.
  • Maintain a close working relationship with R&D: participate in product reviews, flag platform gaps encountered in the field, and propose concrete changes that would make the platform work better for enterprise customers.
  • Collaborate closely with the AI Solutions Architect to translate domain requirements and architecture into working software.
  • Serve as the primary technical point of contact for customers during implementation engagements.

We are looking for builders who thrive in the room with customers, treat ambiguity as a puzzle, and can switch between writing code and facilitating a stakeholder conversation in the same afternoon.

About YouMinimum Qualifications
  • 5+ years of software engineering experience with a demonstrated ability to write and ship production-quality code.
  • Hands-on experience building with LLM APIs, function calling, tool use, agent frameworks, or RAG pipelines-you have shipped something agentic that real users depended on.
  • Proficiency in Python or another scripting/backend language commonly used in data-intensive environments.
  • Proven ability to integrate with messy, heterogeneous enterprise data environments - undocumented APIs, schema mismatches, auth complexity, and legacy systems that do not behave the way the docs claim.
  • Direct experience with external enterprise customers or technical stakeholders in a consulting or customer-facing capacity - earning trust in the room matters as much as writing code.
  • Strong working knowledge of retail and e-commerce system fundamentals.
  • Strong communication skills - able to translate field learnings and technical findings into actionable input for R&D and product teams.
  • Comfort operating in ambiguous, fast-moving environments where the process is not fully defined.
Preferred Qualifications
  • Prior work in a forward deployed, embedded engineering, or professional services capacity.
  • Background at a startup or early-stage company where you wore multiple hats.
  • Experience in enterprise software implementation, systems integration, or solutions engineering.
  • Exposure to retail tech, e-commerce, or supply chain systems.

#LI-Remote

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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