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Rag Developer Jobs in Oregon (NOW HIRING)

OR · On-site

Collaborate with AI architects and engineering teams to integrate LLMs, RAG pipelines, vector ... databases, and agentic AI solutions into enterprise applications. * Support deployment of AI ...

Senior AI Automation Engineer

OR · Remote

$103K - $136K/yr

Data/RAG Pipeline Design & Management * * Design and automate data flow processes to support AI ... Programming for Automation * Write modular, reusable scripts in Python, Ruby, SQL, or JavaScript to ...

OR · On-site

$122K - $161K/yr

RAG and personalization, agent framework and tool use, evals and guardrails, and LLM application ... Contributions to internal developer tooling, golden path standards, or SDLC process improvements.

Senior DevOps Engineer

OR · On-site +1

$129K - $166K/yr

Experience with LLMs / GenAI workflows (RAG, prompt engineering, fine-tuning) * Familiarity with vector databases (Pinecone, Weaviate, OpenSearch) * Exposure to AIOps or AI-driven automation

OR · On-site

$54.50 - $72/hr

Help productionize the Agentic AI platform: agent observability, RAG, and the context-engineering patterns that keep agents reliable from dev through prod. * Partner with the team to consolidate ...

AI Engineer

OR · On-site +1

Experience building Retrieval-Augmented Generation (RAG) applications and AI Agents. * Experience developing REST APIs using FastAPI or similar frameworks. * Familiarity with Git, Azure DevOps, CI/CD ...

AI Vibe Coding Engineer

OR · Remote

$64K - $72K/yr

Optimize developer productivity through automation and AI tooling * Stay current with emerging AI ... Strong understanding of LLMs, RAG architectures, prompt engineering, AI agents, and MCP Preferred ...

Experience building Retrieval-Augmented Generation (RAG) applications and AI Agents. * Experience developing REST APIs using FastAPI or similar frameworks. * Familiarity with Git, Azure DevOps, CI/CD ...

Help develop retrieval-augmented generation (RAG) pipelines and agent-based workflows. * Build and ... Strong programming skills in Python or another modern programming language. * Understanding of ...

OR · On-site

This spans the user-facing AI layer (Wellness Agent, LLM-driven recommendations, RAG over catalog ... Represent engineering in cross-functional conversations with product, data science, security, and ...

Each day, this developer partners with engineering teams across the organization to identify ... RAG, knowledge search, and workflow automation. Strong knowledge of software development lifecycle ...

OR

$122K - $161K/yr

Design and optimize retrieval-augmented generation (RAG) pipelines, including handling long ... DevOps principles * Review code, identify areas for improvement, and help reduce technical debt

AI Integration: Assist in implementing and testing agentic workflows and advanced RAG (Retrieval ... Solid programming foundation with experience in backend development, specifically C# and .NET.

Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. * Work closely with data engineering teams to build/maintain data pipelines ...

Retrieval-Augmented Generation (RAG) * Feature engineering and model evaluation techniques * Experience working with cloud platforms such as Azure, AWS, or similar ecosystems * Familiarity with data ...

Hands-on experience with AI concepts and technologies including Retrieval-Augmented Generation (RAG), AI Agents / Agentic AI, prompt engineering, vector databases and embeddings, model orchestration ...

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Showing results 1-20

Rag Developer information

What is the difference between Rag Developer vs Textile Technician?

AspectRag DeveloperTextile Technician
CredentialsTypically requires a diploma or degree in textiles or related fieldRequires similar qualifications, often with additional certifications in textile testing
Work EnvironmentFactories, textile mills, production plantsLaboratories, quality control departments, manufacturing facilities
Industry UsageUsed in textile manufacturing to develop and process rags for reuse or recyclingInvolved in testing, quality assurance, and technical support in textile production

Both Rag Developers and Textile Technicians work within the textile industry, often in manufacturing settings. Rag Developers focus on creating and processing recycled rags, while Textile Technicians handle testing and quality control. The roles share similar educational backgrounds and work environments, but their specific responsibilities differ based on their focus within textile production.

What are popular job titles related to Rag Developer jobs in Oregon? For Rag Developer jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Rag Developer jobs? Cities in Oregon with the most Rag Developer job openings:
Infographic showing various Rag Developer job openings in Oregon as of July 2026, with employment types broken down into 100% Contract. Highlights an 60% In-person, and 40% Remote job distribution.

Manager - GenAI Full Stack Developer

Deloitte

Portland, OR • On-site

Other

Re-posted 27 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

57th of 150 rated financial services


Job description

Deloitte professionals help organizations navigate business risks and opportunities across financial, operational, information technology (IT), and regulatory areas. In this Manager role, you will lead teams delivering end-to-end (full stack) Generative AI (GenAI) solutions-including Retrieval-Augmented Generation (RAG) and agentic AI-from strategy and architecture through build, deployment, and adoption.

Recruiting for this role ends on July 31st, 2026


Work you'll do

  • Lead client discovery, requirements, and solution shaping; translate needs into architecture, technical specifications, delivery plans, and acceptance criteria.
  • Design, build, and implement custom AI/GenAI solutions tailored to business workflows and risk considerations.
  • Architect and optimize agentic AI systems (e.g., tool-using agents, multi-step orchestration, multi-agent patterns) and integrate with enterprise platforms.
  • Lead end-to-end RAG implementations including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, orchestration, and evaluation.
  • Drive GenAI model build activities (training, fine-tuning, validation), benchmarking, and continuous improvement of quality, safety, latency, and cost.
  • Oversee model deployment and production operations (monitoring, observability, incident response, iteration).
  • Lead development pods (planning, quality, delivery), including code/design reviews, mentoring, and engineering best practices.
  • Collaborate with cross-functional stakeholders (product, data, security, risk/compliance) to deliver scalable, maintainable solutions.
  • Evaluate emerging GenAI/agent frameworks and cloud services; prototype and recommend fit-for-purpose approaches.

The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.

Qualifications
Required:

  • Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field.
  • 6+ years of relevant experience in software engineering/full stack development and delivering AI/ML or GenAI-enabled solutions.
  • Experience leading teams and delivering client-facing solutions with clear ownership for quality and timelines.
  • Required technical skills (must have):
    • GenAI / NLP / Agentic AI
    • Python programming
    • Natural Language Processing (NLP)
    • Agentic AI, including LangChain, LangGraph, and LlamaIndex
    • RAG (Retrieval-Augmented Generation)
    • Prompt engineering
    • Vector databases (design/usage/integration)
    • Model build + deployment
    • GenAI model build: training, fine-tuning, validation
    • Model deployment (serving patterns, monitoring, iteration)
    • Containers (e.g., Docker)
    • Data engineering + APIs
    • ETL (extract, transform, load) and data engineering (pipelines, quality, preprocessing)
    • FastAPI (or equivalent) to build backend services
    • API development and integration (RESTful services)
    • Full stack engineering
    • JavaScript/TypeScript
    • HTML/CSS plus SASS/LESS
    • UI/UX design principles
    • Front-end frameworks: React, Angular, or Vue
    • Cloud AI/ML services across Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
    • Vertex AI experience
  • You should reside within a commutable distance of your assigned office with the ability to commute daily, if required
  • You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations
  • Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve
  • Limited immigration sponsorship may be available.

Preferred:

  • Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
  • Familiarity with AI/GenAI ethics and governance frameworks and implementing controls in production.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $151,470 to $218,025.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Deloitte professionals help organizations navigate business risks and opportunities across financial, operational, information technology (IT), and regulatory areas. In this Manager role, you will lead teams delivering end-to-end (full stack) Generative AI (GenAI) solutions-including Retrieval-Augmented Generation (RAG) and agentic AI-from strategy and architecture through build, deployment, and adoption.

Recruiting for this role ends on July 31st, 2026


Work you'll do

  • Lead client discovery, requirements, and solution shaping; translate needs into architecture, technical specifications, delivery plans, and acceptance criteria.
  • Design, build, and implement custom AI/GenAI solutions tailored to business workflows and risk considerations.
  • Architect and optimize agentic AI systems (e.g., tool-using agents, multi-step orchestration, multi-agent patterns) and integrate with enterprise platforms.
  • Lead end-to-end RAG implementations including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, orchestration, and evaluation.
  • Drive GenAI model build activities (training, fine-tuning, validation), benchmarking, and continuous improvement of quality, safety, latency, and cost.
  • Oversee model deployment and production operations (monitoring, observability, incident response, iteration).
  • Lead development pods (planning, quality, delivery), including code/design reviews, mentoring, and engineering best practices.
  • Collaborate with cross-functional stakeholders (product, data, security, risk/compliance) to deliver scalable, maintainable solutions.
  • Evaluate emerging GenAI/agent frameworks and cloud services; prototype and recommend fit-for-purpose approaches.

The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.

Qualifications
Required:

  • Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field.
  • 6+ years of relevant experience in software engineering/full stack development and delivering AI/ML or GenAI-enabled solutions.
  • Experience leading teams and delivering client-facing solutions with clear ownership for quality and timelines.
  • Required technical skills (must have):
    • GenAI / NLP / Agentic AI
    • Python programming
    • Natural Language Processing (NLP)
    • Agentic AI, including LangChain, LangGraph, and LlamaIndex
    • RAG (Retrieval-Augmented Generation)
    • Prompt engineering
    • Vector databases (design/usage/integration)
    • Model build + deployment
    • GenAI model build: training, fine-tuning, validation
    • Model deployment (serving patterns, monitoring, iteration)
    • Containers (e.g., Docker)
    • Data engineering + APIs
    • ETL (extract, transform, load) and data engineering (pipelines, quality, preprocessing)
    • FastAPI (or equivalent) to build backend services
    • API development and integration (RESTful services)
    • Full stack engineering
    • JavaScript/TypeScript
    • HTML/CSS plus SASS/LESS
    • UI/UX design principles
    • Front-end frameworks: React, Angular, or Vue
    • Cloud AI/ML services across Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
    • Vertex AI experience
  • You should reside within a commutable distance of your assigned office with the ability to commute daily, if required
  • You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations
  • Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve
  • Limited immigration sponsorship may be available.

Preferred:

  • Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
  • Familiarity with AI/GenAI ethics and governance frameworks and implementing controls in production.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $151,470 to $218,025.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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