ZipRecruiter

Log In

2

Remote Ai Implementation Jobs in Georgia (NOW HIRING)

Iterable

Senior IT Engineer (AI)

Atlanta, GA ยท On-site +1

... remote employees worldwide-we are committed to building a diverse and inclusive workplace. We ... AI Implementation: Experience as an AI practitioner, moving beyond prompting into building with AI ...

next page

Showing results 1-20

All JobsRemote Ai Implementation JobsRemote Ai Implementation Jobs in Georgia

Remote Ai Implementation information

What is a Remote AI Implementation Specialist?

A Remote AI Implementation Specialist is a professional who helps organizations deploy and integrate artificial intelligence (AI) solutions without being physically present on-site. They work remotely to assess business needs, customize AI models, oversee technical setups, and ensure seamless integration with existing systems. These specialists often collaborate with cross-functional teams, provide training, and troubleshoot issues to ensure AI tools deliver maximum value. Their expertise enables companies to adopt advanced AI technologies efficiently, regardless of geographic location.

What is the difference between Remote Ai Implementation vs Data Scientist?

AspectRemote Ai ImplementationData Scientist
Required CredentialsAI certifications, programming skills, knowledge of ML frameworksStatistics, programming, data analysis, often a degree in related field
Work EnvironmentCollaborative teams, project-based, often client-facingResearch-focused, data analysis, model development
Industry UsageTech, finance, healthcare, retailTech, finance, healthcare, academia
Search & Comparison IntentImplementing AI solutions remotelyAnalyzing data, building models

Remote Ai Implementation involves deploying AI solutions across various industries, focusing on technical deployment and integration. Data Scientists analyze data and develop models, often in research or analytical roles. While both roles require programming and AI knowledge, Remote Ai Implementation emphasizes deployment skills, whereas Data Scientists focus on data analysis and model creation.

What are the key skills and qualifications needed to thrive as a Remote AI Implementation Specialist, and why are they important?

To thrive as a Remote AI Implementation Specialist, you need a strong background in computer science, data analysis, and AI/machine learning concepts, often supported by a relevant degree or certification. Proficiency with programming languages (such as Python or R), cloud platforms (like AWS or Azure), and AI frameworks (such as TensorFlow or PyTorch) is essential. Exceptional problem-solving, communication, and project management skills help you collaborate effectively and translate business needs into technical solutions. These skills ensure successful deployment of AI solutions that align with organizational goals while facilitating smooth remote teamwork and client interactions.

What are some common challenges faced when implementing AI solutions remotely, and how can they be addressed?

One common challenge in remote AI implementation is maintaining clear communication and alignment between distributed teams, especially when dealing with complex data and evolving project requirements. To address this, regular virtual meetings, detailed documentation, and collaborative project management tools are essential. Additionally, ensuring secure and efficient access to data and resources can be tricky, so robust cybersecurity protocols and cloud-based platforms are often used. Open feedback channels and cross-functional collaboration also help in quickly resolving technical issues and adapting solutions to client needs.
What are the most commonly searched types of Ai Implementation jobs in Georgia? The most popular types of Ai Implementation jobs in Georgia are:
What are popular job titles related to Remote Ai Implementation jobs in Georgia? For Remote Ai Implementation jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Remote Ai Implementation jobs in Georgia look for? The top searched job categories for Remote Ai Implementation jobs in Georgia are:
What cities in Georgia are hiring for Remote Ai Implementation jobs? Cities in Georgia with the most Remote Ai Implementation job openings:
Remote Ai Implementation jobs near you
Infographic showing various Remote Ai Implementation job openings in Georgia as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Enterprise AI Engineer (GCP)

INFT Solutions Inc

Atlanta, GA โ€ข On-site, Remote

Contractor

Posted 29 days ago

Job description

Job Description: Enterprise AI Engineer (GCP)
Location: Remote / Hybrid Focus: Agentic AI, Data Intelligence, and Enterprise Scale
Role Overview
We are looking for a Principal Enterprise AI Engineer to architect and deliver high-impact AI
solutions within the Google Cloud ecosystem. This role is designed for a technical leader who
can bridge the gap between complex data landscapes and autonomous AI systems. You will lead
the development of Agentic AI frameworks and Data Intelligence platforms that drive
significant digital transformation for global enterprise clients.
Core Responsibilities
๏‚ท Architect Agentic Systems: Design and deploy multi-agent orchestration frameworks
using Vertex AI Agent Builder, LangGraph, or CrewAI to automate complex, multi-step
business workflows.
๏‚ท Master RAG Architectures: Build and optimize high-performance Retrieval-
Augmented Generation (RAG) systems, ensuring LLMs are grounded in enterprise data
across BigQuery and Databricks.
๏‚ท Model Strategy & Optimization: Select and fine-tune models within the Gemini 1.5
family, balancing high-reasoning capabilities (Pro) with high-speed efficiency (Flash) for
production-grade latency.
๏‚ท Legacy Transformation: Lead the strategic migration of legacy analytics logic (e.g.,
SAS environments) into modern, AI-powered cloud architectures.
๏‚ท GTM Collaboration: Work closely with Go-To-Market (GTM) leadership to translate
technical AI roadmaps into measurable business value for C-suite stakeholders.
Required Skill Requirements
1. Agentic AI & Orchestration
๏‚ท Framework Mastery: Expert implementation of LangChain, LangGraph, or
LlamaIndex for stateful, autonomous agent development.
๏‚ท Advanced Prompting: Proficiency in Chain-of-Thought (CoT), ReAct patterns, and
system instruction optimization to ensure reliable model output.
๏‚ท Function Calling: Experience building custom tools that allow LLMs to interact
securely with enterprise APIs and SQL databases.
2. Data Intelligence & Engineering
๏‚ท Hybrid Data Ecosystems: Deep experience integrating Google Cloud AI services with
Databricks (Delta Lake) for unified data intelligence.
๏‚ท Vector Engineering: Proficiency with Vertex AI Vector Search (formerly Matching
Engine) and embedding strategies for large-scale semantic search.
๏‚ท Data Flow: Skill in building scalable pipelines using Dataflow or Spark to process
unstructured data for AI readiness.
3. LLMOps & Production Engineering
๏‚ท Evaluation Frameworks: Ability to build automated "LLM-as-a-judge" evaluation
pipelines to track accuracy, faithfulness, and hallucination rates.
๏‚ท Cloud Infrastructure: Mastery of the Vertex AI suite (Studio, Model Garden, Pipelines)
and Infrastructure as Code (Terraform).
๏‚ท Programming: Expert-level Python (FastAPI, Pydantic) and advanced SQL.
4. Strategic Governance
๏‚ท Responsible AI: Implementation of safety filters, PII redaction, and ethical AI
monitoring.
๏‚ท Business Translation: Ability to convert technical metrics (latency, token costs) into
business KPIs (ROI, process efficiency).
Qualifications
๏‚ท Experience: 8+ years in Software Engineering or Data Science, with at least 3+ years
focused on production-grade AI/ML.
๏‚ท Education: B.S./M.S. in Computer Science, AI, or a related quantitative field.
๏‚ท Certifications: Google Professional Machine Learning Engineer or Professional Cloud
Architect (preferred).
Technology Stack
๏‚ท AI/ML: Vertex AI, Gemini 1.5 Pro/Flash, PyTorch.
๏‚ท Data: BigQuery, Databricks, Vertex Vector Search.
๏‚ท Orchestration: LangGraph, Vertex AI Agent Builder.
๏‚ท DevOps: GitHub Actions, Terraform, Vertex AI Pipelines.