Specialist - AI Integration Engineer

Primary Skills:

• Python Development: Proficiency in Python for developing scripts, automation, and integration tasks.

• APIs: Strong experience in developing, consuming, and integrating RESTful APIs.

• Notebooks: Expertise in using Jupiter Notebooks for data analysis and prototyping AI models.

• Logs: Ability to manage and analyze logs for debugging and monitoring purposes.

• Version Control: Proficiency with Git and GitHub for code versioning and collaboration.

• Project Management Tools: Familiarity with Jira for tracking issues, tasks, and project workflows.

• Cloud Platforms: Knowledge of cloud services (Azure)

• Self-Healing Systems: Understanding of self-healing mechanisms and automation in IT infrastructure.

• Experience in developing and integrating Agentic AI solutions.

Nice to Have Skills:

• Containerization: Familiarity with Docker and Kubernetes for container orchestration.

• Data Engineering: Experience with ETL processes, data pipelines, and data warehousing.

• DevOps: Knowledge of CI/CD pipelines and practices.

• Security: Understanding of security best practices in AI and API integrations.

• NLP: Experience with Natural Language Processing techniques and tools.

Experience Required:

• Intermediate Level: 5+ years of relevant experience in Python development and AI integrations.

• Experience in integrating AI solutions with monitoring and alerting systems.

• Experience with API development and integration.

• Demonstrated ability to work with version control systems like Git and platforms such as GitHub

• Experience in working with logs, debugging, and troubleshooting.

• Exposure to cloud platforms and deploying AI solutions.

• Experience in a collaborative environment with cross-functional teams.

• Strong problem-solving skills and ability to work independently.

Core Responsibilities:

• Implement Self-Healing Mechanisms: Develop and implement self-healing mechanisms to automatically resolve identified issues.

• Collaborate with Cross-Functional Teams: Work closely with data engineers, DevOps, and other stakeholders to ensure seamless integration and operation of AI solutions.

• Debug and Troubleshoot Issues: Manage and analyze logs to debug and troubleshoot any issues that arise.

• Maintain and Update Documentation: Create and maintain comprehensive documentation for developed solutions and integration processes.

• Ensure Code Quality and Version Control: Maintain high code quality standards and manage code versioning using Git and GitHub.

• Stay Updated with AI Trends: Keep abreast of the latest developments in AI, machine learning, and related technologies to continuously improve the solutions.