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Remote Knowledge Engineer Jobs in Oregon (NOW HIRING)

Senior Applied AI Engineer

OR · Remote

$122K - $161K/yr

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Knowledge Engineer * Collaborate with software engineers to improve knowledge ingestion, document ...

... Developers, IT, Project Management Professionals, and more. At NV5 Geospatial, we are a ... Qualifications Knowledge, Skills, and Abilities * Interest in GIS and remote sensing

Substation Engineer - Remote

$98K - $125K/yr

Overview Substation Engineer - (Physical/P&C) - Remote - US At NV5, we understand the intricacies ... Knowledge of Protection and Controls design is a must. * B.S. Degree in Electrical Engineering or ...

$150K - $250K/yr

Senior Back End Engineer - Blockchain (Remote) Location: Remote Worker must live within USA or ... Strong knowledge and experience in internet security networks and/or cryptography * Github ...

... Engineer (PE) to join our Tempe, Arizona office. (This job can be remote.) * Proficient in the ... Proficient with Microsoft Office suite and working knowledge of AutoCAD software * Thorough ...

Sr. Electrical Engineer BESS/PV - Remote

$107K - $139K/yr

Overview Senior Electrical Engineer - (BESS/EV/PV) - (Remote - U.S.) About NV5 NV5's Clean Mobility ... Strong working knowledge of the National Electrical Code (NEC), utility standards, and applicable ...

The BESS Engineer II is responsible for the design, development, and implementation of BESS ... Knowledge ofdesign, integration, and optimization of battery energy storagesystems;includinglithium ...

Senior SCADA Engineer, EPC (Remote)

Bend, OR · On-site +1

$110K - $151K/yr

Mentor junior and mid-level engineers through technical review, knowledge sharing, and standards ... recruiter. #LI-Remote Job Number: J13355 If you're interested in a meaningful career with a ...

Senior SCADA Engineer, EPC (Remote)

Bend, OR · On-site +1

$110K - $151K/yr

Mentor junior and mid-level engineers through technical review, knowledge sharing ... recruiter. #LI-Remote Job Number: J13355 If you're interested in a meaningful career with a ...

Senior SCADA Engineer, EPC (Remote)

OR · On-site +1

$104K - $143K/yr

Mentor junior and mid-level engineers through technical review, knowledge sharing ... recruiter. #LI-Remote Job Number: J13355 If you're interested in a meaningful career with a ...

We are looking for exceptional C++ engineers to join our remote-first, global team and continue to ... You have strong knowledge in database internals and design. * You have experience in performance ...

Extensive knowledge of SQL. * Previously worked in a similar SDET, Release Engineering, or QA role ... Demonstrated ability to work collaboratively, including with remote teams. Ability to learn complex ...

The HV SCADA Engineer II will provide intermediate level engineering support for the design ... Professional technical skills and industry knowledge continue to develop over time. * Staff ...

New

The HV SCADA Engineer II will provide intermediate level engineering support for the design ... Professional technical skills and industry knowledge continue to develop over time. * Staff ...

Staff Engineer - Full Time - Remote

OR · On-site +1

$121K - $161K/yr

Remote: Team members who live within the U.S. but are not local within a commutable distance from ... Share knowledge through design reviews, technical presentations, documentation, and coaching. Cross ...

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Showing results 1-20

Remote Knowledge Engineer information

What are the key skills and qualifications needed to thrive as a remote knowledge engineer?

To excel as a Remote Knowledge Engineer, you generally need expertise in knowledge management, ontologies, data modeling, and a relevant degree in computer science or information science. Familiarity with technical tools such as semantic web technologies (e.g., RDF, OWL), knowledge graph platforms, and query languages like SPARQL is often required. Strong analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating across distributed teams and translating complex information. These skills ensure the creation, organization, and optimization of knowledge systems that support informed decision-making and efficient remote operations.

What is the difference between Remote Knowledge Engineer vs Remote Data Scientist?

AspectRemote Knowledge EngineerRemote Data Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of ontologies and knowledge basesBachelor's or higher in CS, Statistics, or related; proficiency in programming and statistical analysis
Work EnvironmentCollaborates with AI teams, develops knowledge systems, often in tech or AI companiesAnalyzes data, builds models, works in tech, finance, or healthcare sectors
Employer & Industry UsageUsed in AI, knowledge management, and enterprise solutionsCommon in data-driven industries like tech, finance, healthcare

While both roles involve technical expertise, Remote Knowledge Engineers focus on developing and managing knowledge bases and AI systems, whereas Remote Data Scientists analyze data to derive insights. Both roles often work in tech industries and require strong technical backgrounds, but their core responsibilities differ significantly.

What is a remote knowledge engineer?

A Remote Knowledge Engineer is a professional who designs, develops, and maintains systems that organize and manage knowledge, often using artificial intelligence and machine learning. They work from a remote location, leveraging digital tools to gather, structure, and analyze information for organizations. Their responsibilities may include building knowledge graphs, developing ontologies, and ensuring that data is accessible and usable for decision-making. Remote Knowledge Engineers collaborate with subject matter experts, software developers, and data scientists to optimize knowledge management solutions. They play a key role in helping organizations turn complex data into actionable insights, all while working outside of a traditional office environment.

How does a remote knowledge engineer typically collaborate with subject matter experts and development teams?

As a Remote Knowledge Engineer, you will frequently interact with subject matter experts (SMEs) to extract, structure, and validate knowledge for use in AI systems or knowledge bases. Collaboration is often conducted through virtual meetings, shared documentation, and project management tools. You’ll also work closely with developers to integrate structured knowledge into systems and ensure accuracy. Effective communication and the ability to translate complex concepts into structured data formats are key to success in this remote, cross-functional environment.
What job categories do people searching Remote Knowledge Engineer jobs in Oregon look for? The top searched job categories for Remote Knowledge Engineer jobs in Oregon are:
What cities in Oregon are hiring for Remote Knowledge Engineer jobs? Cities in Oregon with the most Remote Knowledge Engineer job openings:
Infographic showing various Remote Knowledge Engineer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

Senior Applied AI Engineer

LTS

OR • Remote

$122K - $161K/yr

Full-time

Posted 8 days ago


Job description

Location: United States - Remote
Clearance: Ability to obtain and maintain a Public Trust

LTS is seeking a highly skilled Senior Applied AI Engineer to focus on continuously improving the intelligence behind the platform. You'll experiment with models, optimize retrieval strategies, refine agent reasoning, evaluate AI performance, and transform emerging AI capabilities into production-ready solutions.

The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today.

Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning.

We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide.

The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.

The platform has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small giving every engineer meaningful ownership, and direct influence over product direction.

We don't simply build AI-powered software-we build software with AI. This is not another chatbot.

Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work.

What You'll Do:

Advance Applied AI Capabilities

  • Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity.
  • Evaluate emerging LLMs, multimodal models, agent frameworks, and AI techniques to identify opportunities for platform advancement.
  • Rapidly prototype new AI capabilities and transition successful experiments into production.

Optimize Agent Performance

  • Improve autonomous and multi-agent workflows through prompt engineering, reasoning optimization, memory strategies, tool selection, and context management.
  • Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies, embeddings, reranking, and grounding techniques.
  • Improve AI response quality through experimentation, benchmarking, and iterative optimization.

Evaluate AI Systems

  • Develop evaluation frameworks that measure accuracy, groundedness, explainability, latency, and overall AI effectiveness.
  • Build benchmark datasets, automated evaluation pipelines, and performance metrics for production AI systems.
  • Analyze AI failures, hallucinations, retrieval gaps, and reasoning errors to drive continuous improvement.

Knowledge Engineer

  • Collaborate with software engineers to improve knowledge ingestion, document processing, semantic search, embeddings, and enterprise knowledge management.
  • Design approaches that maximize retrieval quality across large technical documentation and source code repositories.
  • Improve how AI agents discover, organize, and reason over enterprise knowledge.

Collaborate Across Engineer

  • Partner closely with AI architects, platform engineers, software engineers, and front-end engineers to improve the overall intelligence of the platform.
  • Share research findings, experimental results, and engineering recommendations with cross-functional teams.
  • Help establish best practices for experimentation, evaluation, and AI quality throughout the organization.

What We're Looking For:

  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical discipline (or equivalent professional experience).
  • 5+ years of software engineering, applied AI, machine learning, or AI systems development experience.
  • Demonstrated experience developing production AI applications powered by Large Language Models (LLMs).
  • Experience designing and optimizing Retrieval-Augmented Generation (RAG) systems.
  • Experience with prompt engineering, embeddings, semantic search, vector databases, and knowledge retrieval.
  • Experience evaluating AI model performance and implementing experimentation frameworks.
  • Strong programming skills in Python and experience with modern software engineering practices.
  • Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
  • Experience with using AI coding assistants as part of your daily workflow.
  • Familiarity with REST APIs, cloud-native applications, and distributed software systems.
  • Strong analytical, problem-solving, and communication skills.
  • Intellect and curiosity for AI systems and how they behave.
  • Deep passion for experimenting with new AI techniques.
  • Background in evaluation, explainability, and continuous improvement.
  • Proven success with ownership of difficult technical challenges and collaboration across disciplines.

Nice to Have:

  • Experience optimizing autonomous or multi-agent AI systems.
  • Experience implementing automated AI evaluation frameworks.
  • Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs.
  • Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search.
  • Experience with Responsible AI, AI governance, safety, and explainability.
  • Familiarity with software engineering tools, code intelligence platforms, or developer productivity solutions.
  • Experience supporting healthcare, Federal Government, or other highly regulated environments.
  • Experience using AI coding assistants and autonomous agents as part of daily software development.

What's In It for You?

  • The Opportunity to support high-visibility federal missions
  • A culture that values innovation, growth, and collaboration
  • Access to cutting-edge tools and technologies
  • Comprehensive benefits for you and your family
  • A career path that rewards ambition and performance

If you're ready to push boundaries, sharpen your skills, and join a team that is passionate about building what's next, we'd love to meet you. Apply today and let's build a future together!