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Ai Integration Engineer Jobs in Georgia (NOW HIRING)

Medlytix

QA Engineer

Roswell, GA

You'll work closely with AI Integration engineers and software developers to build robust testing strategies that handle the unique challenges of AI systems, including model validation, data quality ...

New

Medlytix

QA Engineer

Roswell, GA · On-site

You'll work closely with AI Integration engineers and software developers to build robust testing strategies that handle the unique challenges of AI systems, including model validation, data quality ...

New

Amcor

AI Innovation Engineer

Atlanta, GA · On-site

Collaborate with business, engineering, and data stakeholders to drive innovation, userengagement ... AI integration patterns. * Experience with Microsoft Azure, Microsoft Fabric, Azure AI Foundry ...

Bravo17

Lead Systems Engineer (data)

Atlanta, GA · On-site +1

Integrate AI/ML models into data workflows, focusing on automated insight generation, predictive modeling, and the development of innovative user experiences. * Collaborate with cross-functional ...

Iterable

Senior IT Engineer (AI)

Atlanta, GA · On-site +1

$141K - $221K/yr

You'll lead on AI integration work while growing your skills in infrastructure engineering, partnering with Enterprise Security to help shape how we approach AI-assisted development. One of our core ...

Intuit

Staff Backend Software Engineer

Atlanta, GA · On-site

This means seeking out those who can seamlessly integrate AI and emerging technologies to ... Coach and mentor junior engineers on best practices of software engineering, leveraging AI to ...

Intellectt INC

Senior - AI Architect

Atlanta, GA · On-site

Integrate and manage MCP Server for scalable AI infrastructure and agent workflows. * Design and ... Required Skills & Qualifications * 14+ years of overall experience in software engineering ...

Deloitte

AI Engineer Consultant

Atlanta, GA · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Deloitte

AI Engineer Consultant

Atlanta, GA · On-site

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

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Showing results 21-40

All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Georgia

Ai Integration Engineer information

See Georgia salary details

$37.6K

$104.9K

$146.5K

How much do ai integration engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for ai integration engineer in Georgia is $104,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $118,200.00 per year, depending on experience, location, and employer.

What are some common challenges faced by AI integration engineers when deploying machine learning models into existing business systems?

AI Integration Engineers often encounter challenges such as ensuring compatibility between machine learning models and legacy systems, managing data privacy and security, and optimizing model performance for real-time applications. They must also address issues related to model scalability and monitoring, as well as facilitate smooth collaboration between data science, IT, and business teams. Overcoming these challenges requires strong problem-solving skills, effective communication, and a deep understanding of both AI technologies and enterprise infrastructure.

What are the key skills and qualifications needed to thrive as an AI integration engineer, and why are they important?

To thrive as an AI Integration Engineer, you need a solid background in computer science, programming (Python, Java, or similar), and experience with AI/ML frameworks, often supported by a bachelor's degree in a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), API development, and tools like TensorFlow or PyTorch is typically required. Strong problem-solving abilities, collaboration, and clear communication are essential soft skills for bridging technical and business needs. These competencies ensure successful deployment and seamless integration of AI solutions into existing systems, driving innovation and business value.

What is the difference between Ai Integration Engineer vs Data Scientist?

AspectAi Integration EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; certifications in AI/ML toolsBachelor's or higher in CS, Statistics, or related; advanced degrees common
Work EnvironmentDeveloping and deploying AI solutions, integrating AI APIs into applicationsAnalyzing data, building predictive models, interpreting complex datasets
Employer & Industry UsageTech companies, AI service providers, software firmsResearch institutions, tech companies, finance, healthcare

While both roles involve AI, the Ai Integration Engineer focuses on implementing and integrating AI solutions into applications, whereas the Data Scientist analyzes data to develop models and insights. The roles often overlap but differ mainly in their primary focus: deployment versus analysis.

What is an AI integration engineer?

AI Integration Engineers are professionals who specialize in implementing artificial intelligence solutions into existing systems, products, or workflows. They work closely with data scientists, software developers, and business teams to ensure that AI models and technologies are effectively deployed and seamlessly integrated. Their responsibilities often include customizing AI tools, developing APIs, ensuring data compatibility, and monitoring performance post-integration. These engineers play a crucial role in bridging the gap between AI research and practical business applications.

Are AI Integration Engineers highly paid?

AI Integration Engineers typically earn higher-than-average salaries due to their specialized skills in AI systems, programming, and data analysis. Compensation varies based on experience, location, and industry, but they are generally well-compensated compared to many other engineering roles.
What are popular job titles related to Ai Integration Engineer jobs in Georgia? For Ai Integration Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Ai Integration Engineer jobs in Georgia look for? The top searched job categories for Ai Integration Engineer jobs in Georgia are:
What cities in Georgia are hiring for Ai Integration Engineer jobs? Cities in Georgia with the most Ai Integration Engineer job openings:
Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Georgia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $104,936 per year, or $50.5 per hour.

QA Engineer

Medlytix

Roswell, GA

Full-time

Posted yesterday

New

Job description

We're seeking an innovative QA Engineer to join our team. This role goes beyond traditional testing - you'll be at the forefront of using automation frameworks and AI-powered tools to ensure the quality, reliability, and performance of our AI solutions. You'll work closely with AI Integration engineers and software developers to build robust testing strategies that handle the unique challenges of AI systems, including model validation, data quality, and non-deterministic outputs.

Key Responsibilities

Test Automation Development

  • Design, develop, and maintain automated test frameworks using Python and modern testing tools
  • Build end-to-end test suites for APIs, data pipelines, and AI model/MCP endpoints
  • Implement continuous testing practices integrated with CI/CD pipelines
  • Create reusable test libraries and utilities to accelerate testing across projects

AI-Assisted Testing

  • Leverage AI tools (like GitHub Copilot, ChatGPT, or dedicated test generation tools) to accelerate test case creation and code reviews
  • Explore and implement AI-powered testing solutions for test data generation, visual testing, and anomaly detection
  • Experiment with automated test scenario generation using LLMs
  • Use AI tools for log analysis and defect pattern recognition

AI-Specific Testing

  • Develop testing strategies for LLMs including performance, accuracy, and bias detection
  • Test data quality, feature engineering pipelines, and model training workflows
  • Validate model output and monitor for model drift in production
  • Create test datasets that cover edge cases and ensure model robustness

Quality Strategy & Collaboration

  • Define and implement QA best practices and quality metrics for AI products
  • Collaborate with developers to identify testability requirements early in the development cycle
  • Perform code reviews focused on test coverage and quality
  • Document test strategies, test cases, and quality reports

Performance & Security Testing

  • Conduct load and performance testing for AI inference endpoints
  • Identify bottlenecks in data processing and model serving infrastructure
  • Participate in security testing activities focusing on data privacy and model security

Required Qualifications

Education & Experience

  • Bachelor's degree in Computer Science, Engineering, or related field
  • 3-5 years of experience in software quality assurance and test automation
  • Proven experience building and maintaining automation frameworks from scratch
  • Experience testing cloud-based applications and APIs
  • Experience testing machine learning models, agentic data flows and data-intensive applications

Technical Skills

  • Strong proficiency in Python for test automation
  • Hands-on experience with testing frameworks: pytest, unittest, Selenium, or similar
  • Experience with API testing tools: Postman, REST Assured, or Python requests
  • Knowledge of CI/CD tools: GitLab CI, GitHub Actions
  • Familiarity with version control systems (Git)
  • Understanding of SQL and database testing (incl. Data Lake architectures)
  • Experience with containerization (Docker) and orchestration tools
  • Experience with AI-powered testing tools or test generation platforms
  • Experience with cloud platforms: AWS, Azure, or GCP
  • Understanding of microservices architecture and distributed systems
  • Experience with workflow orchestration tools (Airflow, Temporal, Prefect, n8n)
  • Experience mentoring junior QA engineers

What You'll Work With:

Languages: Python, SQL, JavaScript/TypeScript, YAML
Data Tools: Airflow, dbt, Spark, Polars, pyArrow
APIs & Integration: FastAPI, GraphQL, Kafka, Redis, Javascript/Typescript, WASM
AI/ML: OpenAI API, Pydantic AI, Anthropic Claude, LangChain, vector databases, MCP protocol
Cloud: AWS (Lambda, S3, RDS, Bedrock, SageMaker) or equivalent in GCP/Azure
Infrastructure: Docker, Kubernetes, Terraform, GitHub Action


As part of our commitment to quality and excellence, Medlytix will continue to maintain a safe and healthy environment for you by requiring all applicants to submit to a criminal history check and those tentatively selected for a position to submit to screening for illegal drug use prior to appointment for a job. In addition, applicants may be screened for ability to perform essential functions of some positions.

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