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Remote Knowledge Engineer Jobs in Boston, MA (NOW HIRING)

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Knowledge of secure coding practices, security frameworks, and tooling (e.g., OWASP, NIST, CIS ...

Contribute to internal knowledge base documentation and troubleshooting guides * Help identify ... Experience working with ticketing systems and remote support tools * Comfortable analyzing logs ...

New

We are open to remote candidates. In this role, the Environmental Engineer is responsible for ... Knowledge of environmental prevention and management plans (e.g., SPCC, SWPPP, Wastewater O&M)

Showing results 21-40

Remote Knowledge Engineer information

See Boston, MA salary details

$41.3K

$125.9K

$208K

How much do remote knowledge engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote knowledge engineer in Boston, MA is $125,875.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,200.00 and $164,600.00 per year, depending on experience, location, and employer.

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.

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.

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 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 job categories do people searching Remote Knowledge Engineer jobs in Boston, MA look for?

The top searched job categories for Remote Knowledge Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Remote Knowledge Engineer jobs?

Cities near Boston, MA with the most Remote Knowledge Engineer job openings:

Infographic showing various Remote Knowledge Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 18% Part Time, 1% Temporary, and 4% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $125,875 per year, or $60.5 per hour.

Building Controls Application Engineer

Mantis Innovation

Boston, MA • Remote

$120K - $130K/yr

Full-time

Re-posted 28 days ago


Job description

Position: Controls Application Engineer 
Start Date: Immediate 
 
As a Controls Application Engineer, you will be responsible for developing BMS/SCADA applications at both a supervisory and controller level. You will help refine engineering standards and provide remote support to project and field teams. You will also be involved in providing support across multiple engineering functions within the Controls Engineering group. You should be familiar with both DDC and PLC programming, BACnet & Modbus integrations, and have experience with building graphical front-end client interfaces.
Controls Application Engineering
  • This position will report to the Controls Engineering Manager.
  • Develop BMS applications across multiple platforms: e.g., Niagara, Ignition, Wonderware, Distech, PLC's.
  • Support the development and enforcement of engineering standards for programming, graphics, alarming, tagging, history management, and database creation. 
  • Provide remote technical support to Project Managers and Field Engineers during project execution. 
Qualifications
  • 10+ years of experience in the engineering field, preferably in Building Automation or Controls Engineering. 
  • 5+ years of BMS application development experience, with mission critical experience preferred. 
  • Strong knowledge of DDC control theory & HVAC applications and the ability to apply these principles to real-world scenarios. 
  • Basic networking knowledge; addressing & subnetting, IP + serial device configurations.
  • Comfortable working with industry standard protocol integrations such as: BACnet, Modbus, Ethernet/IP, SNMP, MQTT.
  • Basic networking knowledge, including manipulating PC settings to set up and commission devices on a network. 
  • Experience with servers, network equipment, and IoT practices, specifically for BMS applications. 
  • 2+ years of experience with Niagara platform (Niagara N4 certification is preferred).
  • Familiarity with Distech field controllers and GFX programming, Ignition SCADA, Wonderware, and PLC systems.
  • Proficiency in Microsoft Office Suite.
Competencies
  • Must be able to work independently and in a team, handling multiple tasks across different projects. 
  • Strong troubleshooting skills, with the ability to identify problems and develop effective solutions. 
  • Knowledge of the construction contracting industry, especially in MEP fields, with experience in mission-critical environments a plus. 
  • Understanding of Mechanical and Electrical equipment in typical Mission Critical environments.
$120,000 - $130,000 a year
This role will provide the opportunity to work in a dynamic and fast-paced environment, where you will gain valuable experience with cutting-edge technologies and play a pivotal role in the successful completion of projects 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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