AI Integration Engineer

Creative Chaos; United States; Remote; USD 110,000 - 150,000; Full time

Job summary

Creative Chaos seeks an AI Integration Engineer to embed AI models into existing systems and workflows, driving enhanced business capabilities and product performance. You will collaborate with AI research, development, and product teams to deliver scalable, robust AI-powered solutions.

In this role, you will design APIs and middleware, ensure production readiness, and optimize data pipelines for accuracy and efficiency. Strong collaboration and learning mindset are essential for success.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or related field.
• 3+ years of experience in integrating AI/ML models into production systems.
• Strong programming skills in Python, Java, or similar languages.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with API development, RESTful services, and microservices architecture.
• Knowledge of cloud platforms and deployment tools (AWS, Azure, Google Cloud).
• Understanding of data pipelines, ETL processes, and data engineering concepts.
• Ability to troubleshoot and optimize AI integration performance.
• Excellent communication and collaboration skills.
• Proactive attitude towards learning new technologies and continuous improvement.

Responsibilities

• Integrate AI and machine learning models into production environments and business applications.
• Collaborate with data scientists, software engineers, and product teams to design integration strategies.
• Develop APIs, middleware, and interfaces to enable seamless AI model deployment and usage.
• Ensure the scalability, reliability, and performance of AI integrations in real-world applications.
• Monitor and troubleshoot AI system performance, identifying and resolving integration issues.
• Optimize AI workflows and data pipelines to improve efficiency and accuracy.
• Maintain documentation related to integration processes, architectures, and configurations.
• Stay updated with emerging AI technologies and recommend new integration approaches.
• Support the deployment and maintenance of AI-based solutions across various platforms.

Skills

Python

Java

TensorFlow

PyTorch

scikit-learn

REST APIs

Microservices

Cloud platforms

ETL pipelines

Education

Bachelor’s or Master’s degree in Computer Science, AI, or related field

Job description

Job Summary:
Creative Chaos is seeking an AI Integration Engineer to join our team. In this role, you will be responsible for integrating AI models and technologies into existing systems and workflows to enhance business capabilities and product performance. You will work closely with AI research, development teams, and product managers to deliver scalable and robust AI-powered solutions.

Key Responsibilities:

• Integrate AI and machine learning models into production environments and business applications.
• Collaborate with data scientists, software engineers, and product teams to design integration strategies.
• Develop APIs, middleware, and interfaces to enable seamless AI model deployment and usage.
• Ensure the scalability, reliability, and performance of AI integrations in real-world applications.
• Monitor and troubleshoot AI system performance, identifying and resolving integration issues.
• Optimize AI workflows and data pipelines to improve efficiency and accuracy.
• Maintain documentation related to integration processes, architectures, and configurations.
• Stay updated with emerging AI technologies and recommend new integration approaches.
• Support the deployment and maintenance of AI-based solutions across various platforms.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field.
• 3+ years of experience in integrating AI/ML models into production systems.
• Strong programming skills in Python, Java, or similar languages.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with API development, RESTful services, and microservices architecture.
• Knowledge of cloud platforms and deployment tools (AWS, Azure, Google Cloud).
• Understanding of data pipelines, ETL processes, and data engineering concepts.
• Ability to troubleshoot and optimize AI integration performance.
• Excellent communication and collaboration skills.
• Proactive attitude towards learning new technologies and continuous improvement.