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Ai Rag Jobs in Seattle, WA (NOW HIRING)

Architect and implement the foundational platform for Agentic and classic AI, encompassing model orchestration, retrieval-augmented generation (RAG), memory systems, and Agent-to-Agent (A2A ...

Senior AI Software Engineer

Kent, WA · On-site

$98.81 - $148.15/hr

Build and maintain RAG pipelines leveraging vector databases to enable intelligent search and retrieval * Develop comprehensive evaluation frameworks (evals) to measure, monitor, and improve AI ...

SRE Engineer -AI

Redmond, WA · On-site

$63.75 - $84.75/hr

Deploy and manage AI resources on Microsoft Azure, including AI Foundry and RAG solutions Monitor and ensure service uptime, availability, reliability, and latency Track and integrate SRE metrics ...

AI Security Engineer

Seattle, WA · On-site

$88 - $142/hr

## AI Security EngineerApplylocations: Seattle, WAtime type: Full timeposted on: Posted Yesterdayjob ... including RAG data isolation, least-privilege tool/function-call authorization, agent action ...

New

The AI Security Engineer exists to secure the university's AI platforms, primarily Purple, built on ... including RAG data isolation, least-privilege tool/function-call authorization, agent action ...

Lead AI Engineer

Bellevue, WA · On-site

$155K - $167K/yr

What you'll do: Lead AI Engineer in the Platforms and Products will... We are seeking a highly ... Build and optimize RAG pipelines using embeddings, chunking strategies, and vector search.

Software Engineer III - Applied AI

Seattle, WA · On-site +1

$65.50 - $88/hr

Lead full-stack development of search, RAG (Retrieval-Augmented Generation), and agentic AI applications using Python, TypeScript/React, and Java * Own retrieval pipeline quality: design and maintain ...

The AI Agent Builder is a core technical role within the AI Platforms team, focused on the design ... Architect and implement advanced RAG pipelines, including embedding strategies, vector search ...

Define technical architecture and roadmap for AI capabilities in support workflows: retrieval-augmented generation (RAG), LLM-based assistants, intent classification, summarization, knowledge ...

The AI Agent Builder is a core technical role within the AI Platforms team, focused on the design ... Architect and implement advanced RAG pipelines, including embedding strategies, vector search ...

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ...

Showing results 41-60

Ai Rag information

See Seattle, WA salary details

$36.4K

$66.3K

$95K

How much do ai rag jobs pay per year?

As of Aug 14, 2026, the average yearly pay for ai rag in Seattle, WA is $66,285.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,800.00 and $74,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

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 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 is an AI RAG?

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 are common challenges faced by AI RAG 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 popular job titles related to Ai Rag jobs in Seattle, WA?

For Ai Rag jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Ai Rag jobs in Seattle, WA look for?

The top searched job categories for Ai Rag jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Ai Rag jobs?

Cities near Seattle, WA with the most Ai Rag job openings:

Infographic showing various Ai Rag job openings in Seattle, WA as of August 2026, with employment types broken down into 77% Full Time, 19% Part Time, and 4% Contract. Highlights an 72% Physical, 4% Hybrid, and 24% Remote job distribution, with an average salary of $66,285 per year, or $31.9 per hour.

Senior AI Architect

Weyerhaeuser Company

Seattle, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago


Weyerhaeuser rating

7.9

Company rating: 7.9 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

8th of 19 rated forestry and logging companies


Job description

Weyerhaeuser is a recognized leader in sustainable forestry and wood products, committed to innovation, operational excellence, and responsible stewardship. As Senior AI Architect, you will define and evangelize AI architectures that power Weyerhaeuser's digital transformation. Spanning traditional machine learning, generative AI, and agentic AI, this role ensures solutions are scalable, secure, and responsible - driving measurable business value across our timberlands, wood products, and corporate functions.

You will partner with business, data, and technology leaders - and external partners - to design and operationalize enterprise AI architectures built on governed, high-quality data. Your work will integrate AI models, services, and agents with technologies such as Microsoft Copilot, Azure, OpenAI, AWS, SAP, and Snowflake, ensuring alignment with Weyerhaeuser's Responsible AI and governance standards. Acting as a bridge between innovation and implementation, you'll enable scalable, trustworthy AI adoption across the enterprise - from supply chain optimization to geospatial and industrial automation.

Key Responsibilities

 

  • AI Architecture Leadership: Define and evolve Weyerhaeuser's enterprise AI and agentic architecture to enable scalable, secure, and interoperable AI solutions across business domains. Establish standards for multi-agent ecosystems, generative AI reasoning pipelines, and MCP-based interoperability to support dynamic, context-aware AI applications that deliver measurable business outcomes.

  • AI Platform and Framework Design: Architect and implement the foundational platform for Agentic and classic AI, encompassing model orchestration, retrieval-augmented generation (RAG), memory systems, and Agent-to-Agent (A2A) communication frameworks. This includes support for traditional machine learning and optimization models that remain critical for forecasting, control, and decision-support use cases. Ensure alignment with enterprise data platforms, governance standards, and Responsible AI principles while enabling experimentation, automation, and adaptive learning across ML models, generative systems, and intelligent agents.

  • Cross-Functional Collaboration: Partner with business, data, product, and engineering teams (internal and external) to translate business opportunities into technical architectures that accelerate AI delivery. Collaborate with IT, cybersecurity, and enterprise architects to ensure AI systems integrate safely and sustainably within Weyerhaeuser's technology ecosystem.

  • Mentorship and Evangelism: Guide engineers, data scientists, and solution architects in applying architectural best practices for AI and MLOps. Evangelize AI innovation through internal knowledge sharing, cross-functional partnerships, and external collaborations.

  • Responsible and Governed AI: Embed Weyerhaeuser's Responsible AI principles - including safety, transparency, sustainability, and accountability - into every stage of the AI lifecycle. Bolster governance practices covering model lineage, monitoring, explainability, and continuous improvement.

  • AI Systems Integration: Architect and oversee the integration of AI models, services, and agents into enterprise systems such as SAP, ServiceNow, Snowflake, and Azure, ensuring interoperability, reliability, and performance across applications, data, and workflows.

  • Innovation and Scalability: Evaluate and prototype emerging AI technologies - including multi-agent systems, large language models, and generative AI platforms - to identify new opportunities for operational excellence and workforce augmentation.

  • Standards, Tools, and Best Practices: Define and promote development standards, reusable components, and reference architectures that enable consistency, security, and speed across all AI initiatives. Champion modular, cloud-native, and API-driven design principles.

  • Performance and Cost Optimization: Design architectures that balance compute efficiency, latency, and cost, ensuring AI systems deliver sustained business value at scale.

Education: Bachelor's degree in Computer Science, Engineering, or a related field; Master's or PhD in AI, Data Science, or a similar discipline preferred.

Experience: 8 years of experience in AI architecture, data science, or software engineering, including large-scale production deployments of machine learning, deep learning, or AI-driven systems in enterprise environments.

Architecture & Integration: Demonstrated ability to design cloud-native and edge AI architectures, integrating models, APIs, and agents into enterprise technology such as SAP, ServiceNow, Snowflake, AWS, and Azure. Proficiency with multi-agent orchestration using Model Context Protocol (MCP), Agent-to-Agent (A2A) interaction models, retrieval-augmented generation (RAG), vector databases, and context memory architectures.

Technical Expertise: Proven experience designing and implementing enterprise-grade AI platforms leveraging both classic ML techniques (forecasting, optimization, predictive modeling) and modern generative and agentic frameworks. Proficiency with cloud-scale AI ecosystems such as Microsoft Copilot Azure, OpenAI, AWS, or GCP, and strong familiarity with Snowflake, SAP, and modern data-governance platforms.

Programming & Tools: Proficiency in Python and familiarity with SQL, R, or Java. Hands-on experience with frameworks such as PyTorch, TensorFlow, scikit-learn, XGBoost, and Hugging Face, and workflow orchestration or MLOps tools (e.g., MLflow, Kubeflow, Airflow).

Industrial & Edge AI: Experience deploying AI in manufacturing or field environments using IIoT data, sensor networks, and edge-compute platforms to enable real-time optimization and automation.

Geospatial AI: Awareness of geospatial data and AI applications (e.g., LiDAR, satellite imagery, and ESRI platforms) and how they inform resource management, sustainability, and operational planning.

Governance & Responsible AI: Experience implementing governance, monitoring, and Responsible AI practices that ensure safety, transparency, and reliability.

Collaboration & Leadership: Strong communicator and collaborator with the ability to translate business goals into technical architectures and influence cross-functional teams.

Strategic Mindset: Ability to align AI architecture decisions with business outcomes, operational efficiency, and sustainability objectives.

Continuous Learning: Committed to staying current with advances in AI, industrial automation, geospatial analytics, and cloud-edge integration.

Compensation: This role is eligible for our annual merit-increase program, and we are targeting a salary range of $135,500-$203,300 based on your level of skills, qualifications and experience. You will also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 25% of base pay. Potential plan funding may range from zero to two times that target.

This position is also eligible to receive between $32,000 in restrictive stock units on an annual basis, as part of our Long Term Incentive Plan.

Benefits: When you join our team, you and your dependents will be offered coverage under our comprehensive employee benefits plan, which includes medical, dental, vision, short and long-term disability, and life insurance.  We offer a pre-tax Health Savings Account option which includes a company contribution.  Other benefit options are also available such as voluntary Long-Term Care and Employee Assistance Programs. We also support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities to help you chart your path to a fulfilling career. 

Retirement: Employees are able to enroll in our company's 401k plan, which includes a paid company match in addition to our annual contribution equal to 5% of your base salary.

Paid Time Off or Vacation: We provide eligible employees who are scheduled to work 25 hours or more per week with 3-weeks of paid vacation to use during your first year of employment.  We also recognize eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees.

Attention Internal Applicants: To ensure transparency across the organization, please have a discussion with your manager prior to applying for any new opportunities. If you need any help facilitating this conversation, please reach out to your HR Representative for guidance. For more information on how to apply, including best practices for updating your profile or partnering with HR and Recruiting, please visit our internal applicant page on Roots: wy.com/applicants 

Weyerhaeuser is an equal opportunity employer. Inclusion is one of our five core values and we strive to maintain a culture where all our people feel a sense of belonging, opportunity and shared purpose. We are committed to recruiting a diverse workforce and supporting an equitable and inclusive environment that inspires people of all backgrounds to join, stay and thrive with our team.

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About Weyerhaeuser

Sourced by ZipRecruiter

Weyerhaeuser is a leading international forest products company based in Seattle, WA, US. Established in 1900, the company has grown to become one of the largest timberland owners in the world. Weyerhaeuser is deeply rooted in the forestry industry and excels in timberland management, as well as the manufacture and distribution of a diverse range of forest products. The product slate encompasses lumber, plywood, wood chips, and other wood-derived materials predominantly used in construction, cellulose fiber production, and bioenergy.

Industry

Manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Seattle, WA, US

Year founded

1900

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