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Assistant Semantic Web Jobs (NOW HIRING)

... semantic HTML and SCSS. The right candidate is going to be a fast learner with good instincts and ... Participate in code review and follow coding standards. * Assist with planning and executing ...

... semantic HTML and SCSS. The right candidate is going to be a fast learner with good instincts and ... Participate in code review and follow coding standards. * Assist with planning and executing ...

Be Seen First

... Assist in remapping article content to an updated tagging system. · Identify and implement ... semantic markup, anchor text, indexability, alt text, etc.) · Contribute to monthly SEO and AI ...

New

Analytic Methodologist

Washington, DC · On-site

$99K - $225K/yr

Experience applying semantic web standards to knowledge model entities, relationships, and ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

Analytic Methodologist

Washington, DC · Hybrid

$99K - $225K/yr

Experience applying semantic web standards to knowledge model entities, relationships, and ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

... assist warfighters in making data visible, accessible, understandable, linked, trustworthy ... semantic web and graph database.  * Well-versed in a variety of NoSQL and relational database ...

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Assistant Semantic Web information

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How much do assistant semantic web jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for assistant semantic web in the United States is $21.30, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Assistant Semantic Web vs Data Analyst?

AspectAssistant Semantic WebData Analyst
Required CredentialsRelevant certifications in semantic web technologies, such as RDF, OWL, SPARQLDegree in statistics, mathematics, or related fields; often certifications in data analysis tools
Work EnvironmentTech companies, research institutions, or organizations implementing semantic web solutionsBusiness, finance, healthcare, and other industries analyzing data for insights
Employer & Industry UsageUsed in semantic web projects, knowledge graphs, and linked data initiativesUsed across industries for data reporting, visualization, and decision-making
Common Search & ComparisonOften compared for technical skills and web technologiesCompared for data handling and analytical skills

The Assistant Semantic Web focuses on developing and managing semantic web technologies, while Data Analysts interpret data to inform business decisions. Both roles require analytical skills but differ in technical focus and industry applications.

More about Assistant Semantic Web jobs
What cities are hiring for Assistant Semantic Web jobs? Cities with the most Assistant Semantic Web job openings:
What are the most commonly searched types of Semantic Web jobs? The most popular types of Semantic Web jobs are:
What states have the most Assistant Semantic Web jobs? States with the most job openings for Assistant Semantic Web jobs include:
Infographic showing various Assistant Semantic Web job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $44,313 per year, or $21.3 per hour.
AI & GEO Solutions Engineer

AI & GEO Solutions Engineer

SNI Technology

Winter Garden, FL • On-site

$130K - $140K/yr

Other

Posted 6 days ago

New


Job description

AI Solutions Engineer / AI Applications Developer
Location: Onsite in Orlando
Pay Range: $130,000-$140,000
Please Note: NO C2C, Agency referrals or sponsorship available
Position Overview:
This role is responsible for designing, developing, and supporting AI-enabled capabilities across web platforms, e-commerce systems, and enterprise applications. The position partners closely with cross-functional teams to enhance AI-driven discoverability, user engagement, and business workflows while ensuring responsible and scalable AI implementation.
Key Responsibilities
  • Analyze, design, develop, test, deploy, and document AI-powered enhancements across websites, e-commerce platforms, intranet applications, APIs, and enterprise systems
  • Support Generative Engine Optimization (GEO) initiatives to improve AI model discoverability, AI-generated brand visibility, and semantic search performance
  • Collaborate with Web, Marketing, Product, Content, SEO/GEO, and Technology teams to optimize structured content, metadata, schema markup, and AI-readable content frameworks
  • Evaluate, configure, integrate, and maintain third-party AI platforms, LLM-based systems, APIs, chatbot tools, knowledge bases, vector search solutions, and workflow automation technologies
  • Design and support AI-driven engagement solutions such as intelligent search, AI assistants, recommendation engines, conversational interfaces, and knowledge retrieval systems
  • Implement and support structured data frameworks including schema standards, embeddings, retrieval-augmented generation (RAG), vector databases, and semantic search architectures
  • Translate business objectives into technical requirements, implementation plans, testing strategies, documentation, and development-ready tasks
  • Act as a liaison between business stakeholders and technical teams for AI initiatives, including requirements gathering, workflow design, testing coordination, and deployment
  • Monitor competitive AI presence, AI-search trends, and evolving AI discovery and commerce strategies
  • Assess AI tools for privacy, security, performance, hallucination risks, data governance, and operational considerations prior to implementation
  • Support enterprise AI governance initiatives, including data stewardship, approval workflows, and responsible AI standards
  • Research emerging AI technologies, platforms, and industry trends relevant to digital commerce, customer engagement, and enterprise operations
  • Drive measurable improvements in AI visibility, semantic discoverability, workflow automation, and AI-assisted user experience

Required Skills & Competencies
  • Strong analytical, problem-solving, and organizational skills
  • Excellent communication skills with the ability to translate technical concepts into business language
  • Ability to work both independently and collaboratively in cross-functional environments
  • Strong project management and prioritization capabilities in fast-paced settings

AI & Technical Knowledge
  • Solid understanding of:
  • Large Language Models (LLMs)
  • Prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • Embeddings and vector search
  • Semantic search and AI orchestration workflows
  • AI testing and evaluation frameworks
  • Knowledge of:
  • Generative Engine Optimization (GEO) and technical SEO
  • Semantic web architecture and structured content optimization
  • AI governance, privacy, security, bias mitigation, and responsible AI practices

Technology Familiarity
Experience with or exposure to tools and platforms such as:
  • OpenAI, Anthropic, Google Gemini
  • AWS Bedrock, Azure AI, Vertex AI
  • LangChain, LlamaIndex
  • Vector databases (e.g., Pinecone, Weaviate)

Nice to have: Experience with enterprise ERP or commerce platforms and integrations
Minimum Qualifications
  • Bachelor's degree in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, or a related field
  • 5+ years of experience developing or supporting enterprise web applications, APIs, or business systems
  • 2+ years of hands-on experience working with AI tools, LLM systems, AI APIs, or automation platforms
  • 5+ years of experience integrating third-party systems using REST APIs, SDKs, and modern integration frameworks
  • Experience with modern web technologies such as JavaScript, TypeScript, HTML/CSS, front-end frameworks, and back-end development (e.g., Java, C#, .NET, Node.js)
  • Experience with relational databases, SQL, and enterprise data models

Preferred Experience
  • Hands-on experience with:
  • AI integrations and workflows
  • Semantic search and vector databases
  • Chatbots and conversational AI
  • Knowledge retrieval systems and AI orchestration pipelines
  • Familiarity with:
  • Structured data and schema markup
  • AI indexing, semantic architecture, and SEO/GEO concepts
  • Cloud deployment, monitoring, and enterprise application support tools (e.g., Git, Jira, Postman)

Additional Requirements
  • Proven ability to gather requirements, identify gaps, and translate business needs into actionable plans
  • Strong collaboration skills across technical teams, business stakeholders, and external partners
  • Awareness of AI privacy, compliance, security, and risk management considerations
  • Ability to stay current with rapidly evolving AI technologies and industry trends
  • Comfortable working in dynamic environments with shifting priorities and emerging technologies
#SNIT