Description:
As an AI Integration Engineer, you will be responsible for integrating AI/ML models into existing systems and workflows, building APIs, optimizing performance, and ensuring smooth deployment and scalability of AI solutions. You’ll work closely with cloud engineer, cybersecurity engineers, data scientists, software engineers, and managed services teams to deliver AI-driven features that power our core services.
Key Responsibilities
- Design, develop, and maintain APIs and services that integrate AI models into production environments.
- Collaborate with teams to understand model requirements and translate them into scalable solutions.
- Deploy and monitor AI models in cloud, on-premises, or edge environments.
- Ensure robust logging, versioning, and monitoring of AI systems in production.
- Optimize system performance and ensure low-latency responses for real-time AI applications.
- Work with cross-functional teams to understand user needs and business goals.
- Contribute to architecture decisions and best practices for AI deployment and integration.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, AI/ML, or related field (or equivalent practical experience).
- 3+ years of experience in backend or systems engineering, preferably with AI/ML model deployment.
- Strong programming skills in Python (preferred), Java, or Node.js.
- Experience with RESTful APIs, microservices, and containerization (Docker, Kubernetes).
- Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model serving tools (e.g., TensorFlow Serving, TorchServe, MLflow).
- Experience deploying models on cloud platforms (AWS, GCP, Azure).
- Strong understanding of CI/CD and DevOps practices for AI workflows.