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Prompt Data Annotation Ai Jobs in Powder Springs, GA

REPAY Company

Data Scientist

Atlanta, GA · On-site

$125 - $150/hr

Design and maintain scalable data-to-AI pipelines covering ingestion, transformation, feature/prompt engineering, model training, orchestration, deployment, and monitoring. * Deliver AI-driven ...

New

YO AI Labs

Korean Language Expert

Atlanta, GA · Remote

$65 - $100/hr

Collaborate with project participants to improve data collection, evaluation, and annotation processes. * Help develop language guidelines and resources tailored to AI training and evaluation.

YO AI Labs

Medical Coder - Remote

Atlanta, GA · Remote

$50 - $80/hr

Collaborate with project teams through written and verbal communication to improve AI training data ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

Worth AI

Senior Agentic (AI) Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

... data. You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment ... Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes.

Siemens Healthineers

AI LLM Engineer

Atlanta, GA · On-site +1

Apply prompt engineering, fine tuning strategies, and model orchestration techniques to improve system performance Data Platform Integration (Snowflake, Fabric, Power BI) * Enable AI systems to ...

Coca-Cola

AI Engineer - Cyber Programs

Atlanta, GA

Test for AI-specific vulnerabilities including prompt injection, jailbreaking, output manipulation, data poisoning, model inversion, training data extraction, membership inference, and adversarial ...

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Prompt Data Annotation Ai information

See Powder Springs, GA salary details

$10

$34

$68

How much do prompt data annotation ai jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for prompt data annotation ai in Powder Springs, GA is $34.33, according to ZipRecruiter salary data. Most workers in this role earn between $22.98 and $37.55 per hour, depending on experience, location, and employer.

What is the difference between Prompt Data Annotation Ai vs Data Labeler?

AspectPrompt Data Annotation AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, often with AI teamsRemote or on-site, often with data teams
Industry UsageAI development, machine learning projectsData management, machine learning datasets
Job FocusAnnotating data for AI prompts and modelsLabeling data for training AI algorithms

Prompt Data Annotation Ai specialists focus on creating high-quality annotations specifically for AI prompts, ensuring models understand context. Data Labelers perform similar tasks but may work on broader datasets. Both roles require attention to detail and are vital in AI development, often overlapping but with different emphasis on prompt-specific annotation versus general data labeling.

What are popular job titles related to Prompt Data Annotation Ai jobs in Powder Springs, GA?

For Prompt Data Annotation Ai jobs in Powder Springs, GA, the most frequently searched job titles are:

What cities near Powder Springs, GA are hiring for Prompt Data Annotation Ai jobs?

Cities near Powder Springs, GA with the most Prompt Data Annotation Ai job openings:

Prompt Data Annotation Ai jobs near you
Infographic showing various Prompt Data Annotation Ai job openings in Powder Springs, GA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $71,409 per year, or $34.3 per hour.

Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas

Atlanta, GA • Remote

$65 - $89/hr

Full-time

Re-posted 22 days ago

Job description

Google Cloud AI Solutions Architect, Gemini Enterprise


Overview

We are seeking a hands-on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and agentic AI solutions for end clients. This is a client-facing technical delivery role focused on applied AI/ML implementation, not sales.

The right candidate will have strong Google Cloud experience, hands-on Gemini Enterprise or Google Cloud generative AI implementation experience, and the ability to translate client workflows into secure, scalable, production-ready AI solutions. This person should be comfortable moving between architecture, coding, prototyping, configuration, integration, and client-facing technical delivery.


Responsibilities

  • Design, build, configure, and implement Gemini Enterprise solutions for end clients.
  • Develop AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows.
  • Build prototypes and proofs of concept that can be iterated into production-ready solutions.
  • Design and implement applied AI/ML solutions using Gemini Enterprise, Vertex AI, and related Google Cloud AI services.
  • Build and deploy LLM-powered applications, AI agents, retrieval-augmented generation workflows, and enterprise AI integrations.
  • Evaluate model options, agent patterns, grounding strategies, retrieval approaches, and integration paths based on client use cases.
  • Configure and deploy Gemini Enterprise agents, integrations, and related Google Cloud AI services.
  • Integrate AI agents with enterprise systems, data sources, APIs, and business applications.
  • Lead technical discovery with clients and translate requirements into solution architecture and implementation plans.
  • Develop scripts, connectors, workflows, or lightweight applications needed to support AI agent implementation.
  • Support model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness.
  • Apply best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment.
  • Communicate technical recommendations clearly to client engineering, data, security, cloud, and business stakeholders.


Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related field; equivalent practical experience will also be considered.
  • 5+ years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or hands-on client-facing technical delivery.
  • 3+ years of experience working with Google Cloud Platform.
  • Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.
  • Hands-on experience implementing Gemini Enterprise or Google Cloud generative AI solutions.
  • Hands-on experience designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or related tools.
  • Experience building, configuring, deploying, or integrating AI agents, generative AI applications, LLM-powered applications, or enterprise AI workflows.
  • Experience building agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or related agent development tools.
  • Experience with core agentic AI implementation patterns such as retrieval-augmented generation, prompt engineering, tool use/function calling, API integrations, enterprise system integration, and/or multi-agent workflows.
  • Experience with LLM application development, embeddings, model evaluation, prompt optimization, and production AI/ML implementation patterns.
  • Strong understanding of Google Cloud AI and data services, such as Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services.
  • Ability to code, script, prototype, and troubleshoot technical solutions in client environments.
  • Experience working directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions.
  • Strong understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices.
  • Excellent communication skills with the ability to explain complex technical concepts clearly.
  • Must be a U.S. Citizen.


Preferred Skills

  • Google Cloud Generative AI Leader certification.
  • Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands-on implementation architect.
  • Experience with Python, JavaScript, TypeScript, or similar programming languages.
  • Experience with data integration, workflow automation, enterprise applications, embeddings, vector search, semantic search, model grounding, enterprise search, or retrieval-augmented generation pipelines.
  • Experience in consulting, systems integration, professional services, or client-facing technical delivery.
  • Familiarity with infrastructure as code, CI/CD, containers, serverless architecture, and cloud-native application deployment.


Additional Information

This position is open to direct candidates only. We are not working with third-party agencies, subcontractors, or C2C arrangements for this role.


Candidates must be U.S. Citizens.