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Knowledge Engineer Jobs in Seattle, WA (NOW HIRING)

You collaborate with business partners, data science and engineering teams to deliver knowledge-based solutions to enable product discoverability for customers. In this role, you will directly impact ...

You collaborate with business partners, data science and engineering teams to deliver knowledge-based solutions to enable product discoverability for customers. In this role, you will directly impact ...

You collaborate with business partners, data science and engineering teams to deliver knowledge-based solutions to enable product discoverability for customers. In this role, you will directly impact ...

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Showing results 1-20

Knowledge Engineer information

See Seattle, WA salary details

$25

$54

$83

How much do knowledge engineer jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for knowledge engineer in Seattle, WA is $54.18, according to ZipRecruiter salary data. Most workers in this role earn between $44.57 and $65.67 per hour, depending on experience, location, and employer.

Which 5 jobs will survive AI?

Knowledge engineers design and refine AI systems by creating data models and algorithms, making their roles less susceptible to automation. Jobs that require complex problem-solving, emotional intelligence, creativity, and specialized expertise—such as healthcare professionals, educators, software developers, researchers, and skilled tradespeople—are more likely to endure AI advancements. Continuous learning and adapting to new tools are essential for these roles to remain relevant.

What are some common challenges Knowledge Engineers face when collaborating with subject matter experts (SMEs)?

Knowledge Engineers often work closely with subject matter experts to extract and formalize complex domain knowledge into structured formats for systems like knowledge bases or AI applications. One common challenge is bridging the communication gap, as SMEs may use specialized jargon or have implicit knowledge that's difficult to articulate. Ensuring accuracy while translating this expertise into machine-readable forms requires patience, active listening, and iterative feedback. Building strong relationships and developing effective questioning techniques are essential for overcoming these challenges and delivering high-quality knowledge models.

What engineers make $500,000?

Senior engineers in fields such as software engineering, data engineering, and specialized roles like machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and stock options. High compensation is often associated with leadership positions, working at large tech companies, or in high-demand industries requiring expertise in cloud computing, AI, or cybersecurity.

What are Knowledge Engineers?

Knowledge Engineers are professionals who design, develop, and maintain systems that simulate human knowledge and reasoning. They work at the intersection of computer science, artificial intelligence, and domain expertise to gather and structure information so that machines can use it to solve complex problems. Their responsibilities often include creating knowledge bases, developing ontologies, and implementing rules or logic to enable decision-making in expert systems or AI applications. Knowledge Engineers play a crucial role in enabling organizations to leverage AI for problem solving and automation.

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze information, create knowledge bases, and use tools like ontologies and rule-based systems to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming are essential for this role.

What is the difference between Knowledge Engineer vs Data Scientist?

AspectKnowledge EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; knowledge of ontologies and knowledge basesBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentTypically in AI development teams, focusing on knowledge systems and expert systemsOften in analytics teams, working with large datasets and predictive modeling
Employer & Industry UsageUsed in AI, robotics, and enterprise knowledge managementCommon in tech, finance, healthcare, and marketing sectors

While both roles involve working with data and information, Knowledge Engineers focus on structuring and encoding knowledge for AI systems, whereas Data Scientists analyze data to extract insights and build predictive models. Their skills and tools differ, but both are essential in data-driven industries.

What engineers make $200,000 a year?

Senior software engineers, data engineers, and certain specialized roles such as machine learning engineers often earn $200,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation can also include bonuses, stock options, and other benefits, depending on the company and location.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

To thrive as a Knowledge Engineer, you need a solid background in computer science, logic, and knowledge representation, often supported by a relevant degree. Familiarity with semantic web technologies, ontology development tools (like Protégé), and knowledge management systems is typically required. Analytical thinking, attention to detail, and strong communication skills help you effectively translate complex information into structured, usable formats. These capabilities ensure that knowledge systems are accurate, interoperable, and valuable for organizational decision-making.

What Is a Knowledge Engineer?

A knowledge engineer works with data and computer systems with the goal of making the technology imitate human thought processes to solve problems that typically require expertise. Working in a sector of artificial intelligence within the information technology field, a knowledge engineer looks at everyday processes and determines what course of thought a human takes to make a decision or begin an activity. They then create computer systems reliant on this extensive data to guide a machine to simulate human cognition and problem-solving. The data validation process is a vital aspect of a knowledge engineer’s job. They must gather an accurate understanding of the tasks at hand and ensure that the data meets specific standards.

What are popular job titles related to Knowledge Engineer jobs in Seattle, WA? For Knowledge Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Knowledge Engineer jobs in Seattle, WA look for? The top searched job categories for Knowledge Engineer jobs in Seattle, WA are:
Infographic showing various Knowledge Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 89% Full Time, 7% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $112,694 per year, or $54.2 per hour.
Principal Knowledge Engineer

Principal Knowledge Engineer

Salesforce, Inc.

Seattle, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 24 days ago


Salesforce rating

8.0

Company rating: 8.0 out of 10

Based on 57 frontline employees who took The Breakroom Quiz

104th of 209 rated software companies


Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

The Experience

Salesforce is building the next generation Enterprise Knowledge Graph platform to power AI-driven experiences, agentic applications, semantic search, enterprise data discovery, and intelligent decision-making across the company. The platform will serve as the foundational knowledge layer connecting enterprise data, business entities, ontologies, and relationships across multiple domains.

We are seeking a Principal Member of Technical Staff (PMTS) to provide technical leadership and architectural direction for Salesforce's Enterprise Knowledge Graph strategy. This role will be responsible for defining the long-term vision, architecture, and execution strategy for Knowledge Graph platforms, semantic technologies, ontology-driven systems, graph data engineering, and AI-powered developer productivity solutions. The PMTS will partner closely with Architecture, Product Management, Ontology, Data Engineering, and AI Platform teams to establish a scalable foundation that supports current and future agentic AI use cases across the enterprise.

In addition to Knowledge Graph leadership, this role will drive the strategy and productionization of AI-powered engineering tools and developer platforms that improve engineering productivity, software quality, operational efficiency, and delivery velocity. The ideal candidate combines deep expertise in Knowledge Graph technologies with a proven track record of leading large-scale technical initiatives and successfully bringing AI-powered engineering solutions from concept to production.

What You'll Actually Be Doing

  • Define and drive the long-term technical vision, architecture, and roadmap for Salesforce's Enterprise Knowledge Graph platform.

  • Lead architecture and design for knowledge graph ecosystems, including graph data models, ontologies, semantic layers, entity resolution frameworks, graph APIs, vector search capabilities, and retrieval architectures supporting AI and agentic use cases.

  • Establish enterprise standards, governance models, engineering patterns, and best practices for Knowledge Graph development, deployment, and lifecycle management.

  • Define strategies for integrating structured, unstructured, and third-party data sources into graph-based platforms using scalable data engineering patterns.

  • Partner with Architecture, Product, AI Platform, and Data Engineering organizations to align platform investments with enterprise priorities and future AI initiatives.

  • Drive technical direction for semantic routing, graph-powered retrieval, enterprise search, agent orchestration, and federated knowledge access patterns.

  • Lead evaluation, selection, and adoption of graph technologies, semantic platforms, vector databases, and AI infrastructure required to support enterprise-scale workloads.

  • Define and drive the strategy for AI-powered developer tooling, engineering automation, and productivity platforms that leverage technologies such as Claude, Cursor, Windsurf, AI Agents, MCP frameworks, and related AI ecosystems.

  • Lead teams in productionizing AI-enabled engineering solutions, ensuring scalability, security, governance, reliability, and measurable productivity improvements.

  • Provide technical leadership and architectural guidance across PMTS, LMTS, SMTS, and contractor teams while driving alignment across multiple organizations.

  • Serve as the primary technical authority for complex architectural decisions, platform investments, and long-term engineering strategy.

  • Foster innovation and continuous improvement while establishing a culture of engineering excellence, technical rigor, and operational maturity.

You're Our Person If...

  • 12+ years of experience in software engineering, data engineering, distributed systems, enterprise data platforms, or related technical domains.

  • A related technical degree required.

  • Proven experience defining and delivering enterprise-scale Knowledge Graph platforms supporting AI, semantic search, data integration, and agentic applications.

  • Deep expertise in Knowledge Graph technologies, ontology engineering, semantic modeling, linked data, graph databases, and enterprise metadata management.

  • Strong hands-on experience with graph technologies such as Neo4j, TopQuadrant, RDF/OWL, SPARQL, property graph models, semantic reasoning frameworks, or similar technologies.

  • Proven experience leading the architecture and implementation of graph-powered AI solutions, semantic retrieval systems, vector search platforms, RAG architectures, and agentic workflows.

  • Demonstrated success in building, scaling, and productionizing AI-powered developer tools, engineering platforms, or automation solutions using technologies such as Claude, Cursor, Windsurf, GitHub Copilot, AI agents, MCP frameworks, or similar ecosystems.

  • Strong experience designing enterprise data engineering architectures, including large-scale ingestion, transformation, orchestration, metadata management, and data governance frameworks.

  • Experience with cloud-native architectures and platforms including AWS, GCP, or Azure.

  • Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.

  • Demonstrated ability to influence senior technical leaders, executives, architects, and cross-functional stakeholders.

  • Proven track record of defining technical strategy and driving execution across multiple teams and organizations.

  • Excellent communication, leadership, and stakeholder management skills.

Even Better If...

  • Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, Information Systems, or a related field.

  • Experience building enterprise Knowledge Graph platforms supporting large-scale AI and agentic ecosystems.

  • Experience with Salesforce Data Cloud, CRM platforms, metadata-driven architectures, or enterprise data platforms.

  • Experience with semantic routing, enterprise search, graph-powered recommendation systems, and intelligent retrieval architectures.

  • Experience with vector databases, Retrieval-Augmented Generation (RAG), AI agents, MCP frameworks, and emerging AI infrastructure technologies.

  • Experience leading enterprise-wide platform initiatives spanning multiple organizations and business domains.

  • Strong understanding of ontology governance, federated knowledge management, and enterprise semantic architecture.

  • Demonstrated track record of driving measurable improvements in engineering productivity through AI-powered tooling and automation.

  • Publications, patents, conference presentations, or recognized industry leadership in Knowledge Graphs, Semantic Technologies, AI Engineering, or related domains.

Unleash Your Potential

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance andbe your best, and our AI agents accelerate your impact so you cando your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates' resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

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