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Ai Rag Jobs in Oregon (NOW HIRING)

Experience with AI RAG/LLM implementations and experience implementing and successfully leveraging agentic AI to accelerate software development Special Requirements/Security Clearance * Ability to ...

Senior Software Engineer

Beaverton, OR · On-site

$127K - $168K/yr

... AI, RAG) • Data Governance Apply at www.Nike.com/Careers (Job# R-84908) #LI-DNI We offer a number of accommodations to complete our interview process including screen readers, sign language ...

Role Summary Build intelligent capabilities using LLM-based inferencing, agentic AI workflows, and RAG-based solutions leveraging AWS-native AI/ML services. Focus on inference orchestration, vector ...

$115K - $231K/yr

Build Retrieval-Augmented Generation (RAG) pipelines, vector search capabilities, and secure data connectors to enable Verathon-owned data usage. * Collaborate with AI Business Partners and other ...

AI Vibe Coding Engineer

OR · Remote

$97K - $133K/yr

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

OR · On-site

$149K - $248K/yr

Lead the design and hands-on development of AI platforms, pipelines, and GenAI / Agentic AI solutions, including LLM-based systems, RAG, MLOps, cloud-native deployment, and scalable agentic ...

Senior Data/AI Engineer

Salem, OR · Remote

$106K - $144K/yr

... generation (RAG), document-level LLM extraction, and agentic frameworks applied to EHR/EMR ... Apply AI and data engineering solutions to diverse healthcare data, including EHR/EMR, practice ...

Collaborate with the AI Infrastructure team to architect robust LLM pipelines, including training workflows and retrieval-augmented generation (RAG) systems * Integrate AI solutions into enterprise ...

Practical experience with AI concepts such as LLMs , retrievalaugmented generation (RAG) , prompt design, and orchestration layers, and how these can be applied in an enterprise context * Experience ...

Collaborate with the AI Infrastructure team to architect robust LLM pipelines, including training workflows and retrieval-augmented generation (RAG) systems * Integrate AI solutions into enterprise ...

OR · On-site

Turn concepts like RAG (retrievalaugmented generation), tool/agent orchestration, evaluation ... AI / Agentic Technical Depth * 5+ years working directly with AI/ML products or platforms (e.g ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

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

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are popular job titles related to Ai Rag jobs in Oregon? For Ai Rag jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Ai Rag jobs? Cities in Oregon with the most Ai Rag job openings:
Chief Solution Architect

Other

Posted 17 days ago


Job description

Company Overview

By Light Professional IT Services LLC readies warfighters and federal agencies with technology and systems engineered to connect, protect, and prepare individuals and teams for whatever comes next. Headquartered in McLean, VA, By Light supports defense, civilian, and commercial IT customers worldwide.

Responsibilities
  • The Chief Solution Architect will provide overall technical leadership and architectural governance for the application maintenance and modernization program, serving as the principal technical authority across all project teams.
  • This individual will establish and maintain enterprise architecture standards, guide the modernization strategy from legacy on-premise systems to AWS cloud services, and ensure technical decisions align with both immediate operational needs and long-term strategic objectives.
  • The Chief Architect will collaborate closely with government technical leads, review and approve major architectural decisions, oversee technical risk management, and ensure that all solutions comply with federal security requirements and GSA enterprise architecture standards while optimizing for performance, scalability, and cost-effectiveness.
Required Experience/Qualifications
  • Bachelor's degree in Computer Science, Information Systems, or related technical field AWS Certified Solutions Architect Professional certification
  • Minimum 8 years' experience in one or more architecture domains (e.g., business architecture, solutions architecture, application architecture)
Preferred Experience/Qualifications
  • Advanced knowledge and experience in one or more current programming languages (e.g., Java, JavaScript (including AngularJS), Python, Rust, Go, or PHP)
  • Experience defining the architecture of cloud deployed applications (AWS preferred)
  • Expertise in service-oriented architecture, web services, and Application Programming Interfaces
  • Experience defining and driving SecDevOps best practices within large teams, including AI assisted code development
  • Experience establishing legacy modernization and migration technical roadmaps for large scale applications
  • Experience building applications using service-oriented, microservice, and/or API based architectures at an enterprise scale
  • Experience with event-driven applications using queues, service bus and other related patterns
  • Experience in working closely with technical leads, engineering teams and architecture stakeholders for technical issues and architecture framework capabilities for use by other development teams
  • Ability to translate technically complex features into plain language for leadership
  • Experience with AI RAG/LLM implementations and experience implementing and successfully leveraging agentic AI to accelerate software development
Special Requirements/Security Clearance
  • Ability to obtain and maintain a Public Trust
Employment Type: OTHER