Knowledge Engineer Jobs
Knowledge Engineer jobs are open from entry-level to senior and principal across technology, healthcare, finance, and consulting, with specializations in ontology design, natural language processing, and knowledge graph development. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 63+ Knowledge Engineer jobs
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies or storage.
- 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
- Experience with Artificial Intelligence, Generative AI, and Generative AI Agents.
- Experience with distributed systems and software architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing Cloud or SaaS products.
- Experience with shipping 0-to-1 AI applications, with a holistic understanding of product, quality, and infra.
- Knowledge of data warehouses, big data, SQL, and data governance.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of the Knowledge Catalog, you will work on the foundational context engine for the AI era. In this role, you will work on an always-on, enterprise-wide catalog for AI that serves as the single source of truth for both human users and AI agents. As a part of the team, you will help bridge the gap between raw data and true business meaning, powering Google's Agentic Data Cloud (demoed at Google Cloud Next ’26 - Agentic Data Cloud) and enabling AI agents to reason, act, and execute on complex enterprise data. You will provide universal business context and governance for your entire data estate as Data teams and AI developers use Knowledge Catalog to discover data, enforce policies, and retrieve rich context for both analytics and autonomous applications.
In this role, you will empower AI agents across industry-leading Google Cloud and third-party data ecosystems (BigQuery, lakehouses, operational databases, etc.).
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies or storage.
- 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
- Experience with Artificial Intelligence, Generative AI, and Generative AI Agents.
- Experience with distributed systems and software architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing Cloud or SaaS products.
- Experience with shipping 0-to-1 AI applications, with a holistic understanding of product, quality, and infra.
- Knowledge of data warehouses, big data, SQL, and data governance.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of the Knowledge Catalog, you will work on the foundational context engine for the AI era. In this role, you will work on an always-on, enterprise-wide catalog for AI that serves as the single source of truth for both human users and AI agents. As a part of the team, you will help bridge the gap between raw data and true business meaning, powering Google's Agentic Data Cloud (demoed at Google Cloud Next ’26 - Agentic Data Cloud) and enabling AI agents to reason, act, and execute on complex enterprise data. You will provide universal business context and governance for your entire data estate as Data teams and AI developers use Knowledge Catalog to discover data, enforce policies, and retrieve rich context for both analytics and autonomous applications.
In this role, you will empower AI agents across industry-leading Google Cloud and third-party data ecosystems (BigQuery, lakehouses, operational databases, etc.).
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
See All 63 Knowledge Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Knowledge Engineer JobsKnowledge Engineer Job Market
Who's Hiring
- Apple13
- TikTok7
- Stellantis4
- Google3
- Remitly2
Top Industries Hiring
- Banking & Financial Services
- Automotive
- Technology & Software
What Employers Look For
The qualifications that appear most often in knowledge engineer jobs.
- Bachelor's or master's degree in computer science, information science, or a related field
- Proficiency in knowledge representation languages such as OWL, RDF, and SPARQL
- Experience designing or maintaining ontologies and knowledge graphs
- Familiarity with natural language processing tools and semantic technologies
- Ability to collaborate with subject-matter experts to elicit and formalize domain knowledge
- Experience with graph database platforms and semantic reasoning frameworks
Tips for Your Knowledge Engineer Job Search
Show ontology work in your resume
Generic AI or data science bullets won't land you interviews. Call out the specific ontologies or knowledge graphs you built or maintained, the domain they covered, and the tools you used to model and query them.
Apply early to roles that fit
Migrate Mate lists knowledge engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings that name your tech stack
Knowledge engineering roles vary widely between organizations. Filter for job titles and descriptions that specifically mention the tools you know, such as OWL, RDF, SPARQL, or graph databases, so your application speaks directly to what they need.
Prepare a domain knowledge narrative
Interviewers for these roles want to know not just how you build knowledge structures but why you made specific modeling decisions. Prepare two or three examples where you chose one representation approach over another and what trade-offs you weighed.
Demonstrate cross-functional collaboration experience
Knowledge engineers rarely work in isolation. Listings consistently ask for experience translating requirements from subject-matter experts into formal models. Highlight projects where you elicited knowledge from non-technical stakeholders and encoded it accurately.
Follow up with a schema or diagram sample
After an interview, sending a small diagram or schema sample relevant to the problem discussed reinforces your technical depth. Keep it concise, well-labeled, and directly tied to something you discussed so it reads as insight, not unsolicited work.
Knowledge Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most knowledge engineers?
The most active employers for knowledge engineers right now are Apple, TikTok, and Stellantis, and the most openings are in California, Washington, and Michigan, based on current listings on Migrate Mate as of November 2026. Demand is especially strong in technology, healthcare IT, and enterprise software companies building AI-driven products.
How many knowledge engineer jobs are remote?
About 72% of knowledge engineer openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed technical talent. Sub-areas focused on ontology development and semantic data modeling tend to offer the highest share of remote arrangements, since the work centers on structured files and version-controlled repositories rather than on-site infrastructure.
How do you become a knowledge engineer?
Start with a foundation in computer science, information science, or linguistics, then build hands-on skills in knowledge representation languages like OWL and RDF. Work through public ontology projects or contribute to open repositories to build a portfolio. From there, apply to roles in organizations that maintain large structured knowledge assets, such as healthcare systems, research labs, or enterprise software companies.
Can you get a knowledge engineer job with little or no experience?
Entry-level roles do exist, particularly at organizations building new knowledge bases rather than maintaining legacy ones. The most effective way to break in is to publish a small domain ontology publicly, contribute to an open-source knowledge graph project, and demonstrate familiarity with at least one graph query language. Employers value evidence of independent, structured thinking over years of tenure.
What does the knowledge engineer interview process look like?
Most processes include an initial screening call, a technical assessment involving ontology or schema design, and a panel interview with engineers and domain experts. The technical stage often asks you to model a real-world domain under time constraints. Panel interviews focus on how you handle ambiguity when translating expert knowledge into formal representations and how you communicate modeling decisions to non-technical stakeholders.
Where can I find and apply to knowledge engineer jobs?
You can find and apply to knowledge engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your skills and experience level, then apply directly to each one that fits. No extra steps are needed between finding a role and submitting your application.
See All 63 Knowledge Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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