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Ai Tagging Jobs (NOW HIRING)

Rockstar

Jr AI Engineer

Help build and maintain RAG workflows, including document preparation, chunking, metadata tagging ... Support debugging of AI workflows, data pipelines, API integrations, and model behavior under the ...

Influur

AI Engineer

San Francisco, CA

$150K - $200K/yr

Past experience in video content classification/embeddings/tagging. You're the Type Who * Builds like an AI native, automates, experiments, and ships at lightning speed. * Brings a generalist mindset ...

Influur

AI Engineer

San Francisco, CA · On-site +1

$150K - $200K/yr

Past experience in video content classification/embeddings/tagging. You're the Type Who * Builds like an AI native, automates, experiments, and ships at lightning speed. * Brings a generalist mindset ...

Influur

AI Engineer

New York, NY · On-site +1

$150K - $200K/yr

Past experience in video content classification/embeddings/tagging. You're the Type Who * Builds like an AI native, automates, experiments, and ships at lightning speed. * Brings a generalist mindset ...

Influur

AI Engineer

New York, NY

$150K - $200K/yr

Past experience in video content classification/embeddings/tagging. You're the Type Who * Builds like an AI native, automates, experiments, and ships at lightning speed. * Brings a generalist mindset ...

Influur

AI Engineer

Mundelein, IL · Remote

Past experience in video content classification/embeddings/tagging. You're the Type Who * Builds like an AI native, automates, experiments, and ships at lightning speed. * Brings a generalist mindset ...

Bandwidth Inc.

AI Knowledge Manager

Raleigh, NC · On-site

... tagging conventions, and metadata standards -- ensuring content is consistently organized and retrievable by human agents, AI systems, and self-serving customers. • Partner with support execution ...

Bandwidth

AI Knowledge Manager

Raleigh, NC · On-site

The AI Knowledge Manage r ensures content in Bandwidth's Support Center and internal knowledge base ... tagging conventions, and metadata standards - ensuring content is consistently organized and ...

Bandwidth

AI Knowledge Manager

Raleigh, NC

The AI Knowledge Manage r ensures content in Bandwidth's Support Center and internal knowledge base ... tagging conventions, and metadata standards -- ensuring content is consistently organized and ...

Apply Early

Bandwidth

AI Knowledge Manager

Raleigh, NC

The AI Knowledge Manage r ensures content in Bandwidth's Support Center and internal knowledge base ... tagging conventions, and metadata standards - ensuring content is consistently organized and ...

Bandwidth

AI Knowledge Manager

Raleigh, NC · On-site

The AI Knowledge Manage r ensures content in Bandwidth's Support Center and internal knowledge base ... tagging conventions, and metadata standards - ensuring content is consistently organized and ...

GDIT

AI Platform Engineer

Concord, NC · Hybrid

$127K - $172K/yr

Maintain conversation-aware context pipelines used for tagging and classification agents. WHAT YOU ... AI-powered career tool that identifies career steps and learning opportunities * Support: An ...

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Ai Tagging information

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$39K

$114.3K

$150K

How much do ai tagging jobs pay per year?

As of Jul 2, 2026, the average yearly pay for ai tagging in the United States is $114,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $134,500.00 per year, depending on experience, location, and employer.

What does a typical day look like for someone in an AI Tagging role?

A typical day for an AI Tagging professional includes reviewing and labeling large sets of data—such as images, audio, or text—according to specific guidelines provided by the project. You may spend time collaborating with data scientists or project managers to clarify labeling instructions or resolve ambiguous cases. Work is usually structured with clear quality and productivity targets, and you might also participate in feedback sessions to improve annotation consistency. The pace can be steady, with periods of high concentration, and you may use specialized software platforms to manage your workflow. Team communication and attention to detail are key aspects of the job each day.

What are the key skills and qualifications needed to thrive in the Ai Tagging position, and why are they important?

To thrive in AI Tagging, you need strong attention to detail, data annotation skills, and familiarity with data quality standards, often backed by experience or coursework in information science or computer science. Familiarity with data labeling platforms, image and text annotation tools, and occasionally basic programming or scripting knowledge is beneficial. Strong organizational skills, patience, and the ability to work efficiently both independently and within a team distinguish top performers in this role. These skills ensure the accurate and efficient creation of high-quality labeled datasets that are essential for training and improving AI models.

What is an AI Tagging job?

An AI Tagging job involves labeling or annotating data to help train machine learning models. This can include tagging images, videos, text, or audio with relevant metadata so that AI systems can recognize patterns and improve accuracy. AI taggers follow specific guidelines to ensure consistency and quality in the annotations. It's a crucial step in developing AI systems for tasks like image recognition, natural language processing, and recommendation algorithms.

More about Ai Tagging jobs
What cities are hiring for Ai Tagging jobs? Cities with the most Ai Tagging job openings:
What are the most commonly searched types of Ai Tagging jobs? The most popular types of Ai Tagging jobs are:
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Ai Tagging jobs near you
Infographic showing various Ai Tagging job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $114,320 per year, or $55 per hour.

Agentic AI / Semantic Solutions Architect

Atika Tech

Atlanta, GA • On-site

Other

Posted 27 days ago

Job description

Position : Agentic AI / Semantic Solutions Architect #19572
Location :  Atlanta, GA, USA (Hybrid on site)
Duration: 12+ Months
Experience : 13+ Years

Role Overview
We are seeking a highly skilled Agentic AI / Semantic Solutions Architect to design and prototype advanced agent-layer architectures that operate on enterprise semantic data platforms. This role sits at the intersection of LLM orchestration, knowledge graphs, and semantic data modeling, focusing on building POC-level intelligent agent solutions rather than production-scale systems.

The ideal candidate will have deep expertise in agent-based AI systems, GraphRAG architectures, and context engineering, with the ability to design frameworks where autonomous agents can effectively interpret and reason over structured knowledge.

Key Responsibilities
Architect and design agentic AI workflows that consume outputs from semantic layers, including knowledge graphs, ontologies, and metadata catalogs
Develop and prototype GraphRAG pipelines that combine graph traversal with vector-based retrieval for accurate, domain-grounded responses
Define and implement context engineering strategies, including metadata injection, chunking, and semantic optimization for LLM prompts
Design and build Model Context Protocol (MCP) server patterns to enable seamless interaction between agents and semantic data systems
Develop LLM orchestration workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or AutoGen
Build pipelines for automated metadata extraction and semantic tagging using NLP and LLM-based approaches
Collaborate with Semantic Data Architects to ensure ontologies and graph structures are optimized for agent traversal and querying
Prototype agent-based solutions for business use cases such as:
Credit risk analysis
Customer data onboarding workflows
 

Mandatory Skills
Strong expertise in Agentic AI architecture (multi-agent systems, tool usage, planning loops)
Hands-on experience with GraphRAG design (hybrid graph + vector retrieval systems)
Experience in LLM orchestration frameworks:
LangChain, LangGraph, LlamaIndex, or AutoGen
Deep understanding of context engineering techniques (chunking, windowing, semantic compression)
Experience designing and integrating Model Context Protocol (MCP)
Strong knowledge of semantic systems such as:
Knowledge graphs
Ontologies
Metadata-driven architectures
Nice to Have Skills
Experience with Google Vertex AI (Agent Builder / Search)
Knowledge of Google Cloud Platform Spanner Graph
Familiarity with metadata platforms like Collibra or Google Dataplex
Experience with vector databases:
Pinecone, Weaviate, pgvector, Vertex AI Vector Search
Prior experience in regulated domains such as financial services or legal systems

Thanks & Regards,

 

Bhupender Singh

XL Impex Inc dba

Atika Technologies

5 Independence Way, Suite 300,

Princeton, NJ 08540

LinkedIn URL: 

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